----------------------------------------------------------------------------------------------------------
      name:  <unnamed>
       log:  C:\Users\wujen\Dropbox\S_CandidateRaceIdeology\Replication Archive\masterlog.log
  log type:  text
 opened on:  22 Aug 2024, 10:49:05

. 
. do 1_clean_data.do

. /*
>         Cleaning script for study 1 and study 2.
>         Identifying variables have been removed from the raw files.
> 
> */
. 
. 
. /*-------------------------------------------
>         Study 1
> ---------------------------------------------*/
. 
. insheet using study_1_raw.csv, comma  clear
(119 vars, 2,467 obs)

. 
. 
. // Demographics
. 
.         gen r_age = age 

.         
.         gen male = gender == 1

.         gen female = gender == 2

. 
.         gen hhi_1 = inrange(hhi, 1, 4) // <30k

.         gen hhi_2 = inrange(hhi, 5, 10) // 30-60k

.         gen hhi_3 = inrange(hhi, 11, 18) // 60-100k

.         gen hhi_4 = inlist(hhi, 19, 20, 21, 22) // 100-200k

.         gen hhi_5 = inlist(hhi, 23, 24) // 200+

.         gen hhi_6 = hhi == -3105 // prefer not say

. 
.         gen edu_nohs = educ == 1

.         gen edu_hs = inlist(educ, 2, 3)

.         gen edu_somecol = educ == 4

.         gen edu_2yr = educ == 5

.         gen edu_ba = educ == 6

.         gen edu_postgrad = inlist(educ, 7, 8)

. 
.         gen reg_ne = region == 1

.         gen reg_mw = region == 2

.         gen reg_s = region == 3

.         gen reg_w = region == 4

.         
. 
. // Respondent Race
.         gen r_white = dem_race == "White"

.         gen r_black = dem_race == "Black or African American"

.         gen r_asian = dem_race == "Asian"

.         gen r_hispanic = dem_race == "Hispanic or Latino"

.         gen r_other = missing(r_white) & missing(r_black) & missing(r_asian) & missing(r_hispanic)

. 
. // Respondent PID
.         rename political_party r_pid

.         gen r_dem = inlist(r_pid, 1, 2, 3, 6)

.         gen r_ind = inlist(r_pid, 4)

.         gen r_gop = inlist(r_pid, 5, 8, 9, 10)

.         label var r_dem "Respondent PID, Democrats (Incl. Leaners)"

.         label var r_ind "Respondent PID, Pure Independents"

.         label var r_gop "Respondent PID, Republicans (Incl. Leaners)"

.         label var r_pid "Respondent PID from Lucid"

. 
.         
. // Candidate Profile Attributes
. 
.         cap confirm numeric variable cattr_age

.         di _rc
0

.         if _rc != 0 gen cand_age = real(cattr_age)

.         if _rc == 0 gen cand_age = cattr_age

.         gen cand_black = cattr_race == "Black"

.         gen cand_white = cattr_race == "White"

.         gen cand_female = cattr_sex == "woman"

.         gen cand_male = cattr_sex == "man"

.         
.         label var cand_age "Candidate Age"

.         label var cand_black "Black"

.         label var cand_white "White"

.         label var cand_female "Female"

.         label var cand_male "Male"

.                 
.         
.         loc attr "cand_policy_abort1 cand_policy_abort2 cand_policy_tax1 cand_policy_tax2 cand_policy_he
> alth1"

.         loc attr2 "cand_policy_health2 cand_policy_eco1 cand_policy_eco2 cand_policy_aa1 cand_policy_aa2
>  cand_policy_aa3"

.         
.         foreach var in `attr' `attr2' {
  2.                 gen `var' = 0
  3.         }

.         /* 
>                 Use key phrases to determine issue area.
>                 strpos return 0 if text is not found, so if !=0, then phrase is in variable
>         */
.         
.         foreach x in a b c {    
  2.                 replace cand_policy_abort2 = 1 if strpos(cattr_policy`x', "first trimester") != 0
  3.                 replace cand_policy_abort1 = 1 if strpos(cattr_policy`x', "including the third trimes
> ter") != 0
  4.                 
.                 replace cand_policy_tax1 = 1 if strpos(cattr_policy`x', "Increase the tax rate") != 0
  5.                 replace cand_policy_tax2 = 1 if strpos(cattr_policy`x', "Maintain the current tax rat
> e") != 0
  6.                 
.                 replace cand_policy_health1 = 1 if strpos(cattr_policy`x', "Expand healthcare coverage")
>  != 0
  7.                 replace cand_policy_health2 = 1 if strpos(cattr_policy`x', "Maintain current governme
> nt") != 0
  8.                 
.                 replace cand_policy_eco1 = 1 if strpos(cattr_policy`x', "Expand investment in renewable"
> ) != 0
  9.                 replace cand_policy_eco2 = 1 if strpos(cattr_policy`x', "Maintain current patterns") 
> != 0
 10.                 
.                 replace cand_policy_aa1 = 1 if strpos(cattr_policy`x', "Expand affirmative action") != 0
 11.                 replace cand_policy_aa2 = 1 if strpos(cattr_policy`x', "Maintain existing affirmative
>  action") != 0
 12.                 replace cand_policy_aa3 = 1 if strpos(cattr_policy`x', "Replace affirmative action") 
> != 0
 13.         }
(197 real changes made)
(213 real changes made)
(210 real changes made)
(225 real changes made)
(207 real changes made)
(190 real changes made)
(187 real changes made)
(203 real changes made)
(208 real changes made)
(195 real changes made)
(234 real changes made)
(174 real changes made)
(198 real changes made)
(224 real changes made)
(198 real changes made)
(226 real changes made)
(216 real changes made)
(200 real changes made)
(206 real changes made)
(211 real changes made)
(199 real changes made)
(211 real changes made)
(217 real changes made)
(226 real changes made)
(196 real changes made)
(214 real changes made)
(207 real changes made)
(187 real changes made)
(208 real changes made)
(205 real changes made)
(201 real changes made)
(176 real changes made)
(211 real changes made)

.                 
.         label var cand_policy_abort1 "Allow abortion, any time"

.         label var cand_policy_abort2 "Allow abortion up to 2nd tri."

.         label var cand_policy_tax1 "Increase tax rate on rich"

.         label var cand_policy_tax2 "Maintain tax rate on rich"

.         label var cand_policy_health1 "Expand health coverage"

.         label var cand_policy_health2 "Maintain health coverage policies"

.         label var cand_policy_eco1 "Expand investment in energy"

.         label var cand_policy_eco2 "Maintain investment in energy"

.         label var cand_policy_aa1 "Expand affirmative action (race)"

.         label var cand_policy_aa2 "Keep affirmative action as is"

.         label var cand_policy_aa3 "Replace affirmative action (class)"

.         
.         // Check that each policy type appears only once
.         egen temp_tax = rowtotal(cand_policy_tax*)

.         egen temp_abort = rowtotal(cand_policy_abort*)

.         egen temp_health = rowtotal(cand_policy_health*)

.         egen temp_eco = rowtotal(cand_policy_eco*)

.         egen temp_aa = rowtotal(cand_policy_aa*)

.         codebook temp_*

----------------------------------------------------------------------------------------------------------
temp_tax                                                                                       (unlabeled)
----------------------------------------------------------------------------------------------------------

                  Type: Numeric (float)

                 Range: [0,1]                         Units: 1
         Unique values: 2                         Missing .: 0/2,467

            Tabulation: Freq.  Value
                        1,200  0
                        1,267  1

----------------------------------------------------------------------------------------------------------
temp_abort                                                                                     (unlabeled)
----------------------------------------------------------------------------------------------------------

                  Type: Numeric (float)

                 Range: [0,1]                         Units: 1
         Unique values: 2                         Missing .: 0/2,467

            Tabulation: Freq.  Value
                        1,242  0
                        1,225  1

----------------------------------------------------------------------------------------------------------
temp_health                                                                                    (unlabeled)
----------------------------------------------------------------------------------------------------------

                  Type: Numeric (float)

                 Range: [0,1]                         Units: 1
         Unique values: 2                         Missing .: 0/2,467

            Tabulation: Freq.  Value
                        1,234  0
                        1,233  1

----------------------------------------------------------------------------------------------------------
temp_eco                                                                                       (unlabeled)
----------------------------------------------------------------------------------------------------------

                  Type: Numeric (float)

                 Range: [0,1]                         Units: 1
         Unique values: 2                         Missing .: 0/2,467

            Tabulation: Freq.  Value
                        1,258  0
                        1,209  1

----------------------------------------------------------------------------------------------------------
temp_aa                                                                                        (unlabeled)
----------------------------------------------------------------------------------------------------------

                  Type: Numeric (float)

                 Range: [0,1]                         Units: 1
         Unique values: 2                         Missing .: 0/2,467

            Tabulation: Freq.  Value
                          621  0
                        1,846  1

.         drop temp_*

.         
.         gen has_racepolicy = (cand_policy_aa1 == 1) | (cand_policy_aa2 == 1) | (cand_policy_aa3 == 1)

.         label var has_racepolicy "Candidate profile has a racial policy"

.         
. // Outcomes on Candidate inferences
.         gen out_ideo_7 = .
(2,467 missing values generated)

.         gen out_ideo_econ = .
(2,467 missing values generated)

.         gen out_ideo_soc = .
(2,467 missing values generated)

.         
.         rename cattr_ideo7 cattr_ideo_7

.         foreach var in econ soc 7 {
  2.                 replace out_ideo_`var' = 1 if cattr_ideo_`var' == "Extremely Liberal"
  3.                 replace out_ideo_`var' = 0.8334 if cattr_ideo_`var' == "Liberal"
  4.                 replace out_ideo_`var' = 0.6667 if cattr_ideo_`var' == "Slightly Liberal"
  5.                 replace out_ideo_`var' = 0.5 if cattr_ideo_`var' == "Moderate"
  6.                 replace out_ideo_`var' = 0.3334 if cattr_ideo_`var' == "Slightly Conservative"
  7.                 replace out_ideo_`var' = 0.1667 if cattr_ideo_`var' == "Conservative"
  8.                 replace out_ideo_`var' = 0 if cattr_ideo_`var' == "Extremely Conservative"
  9.         }
(373 real changes made)
(652 real changes made)
(388 real changes made)
(534 real changes made)
(155 real changes made)
(125 real changes made)
(81 real changes made)
(496 real changes made)
(643 real changes made)
(354 real changes made)
(497 real changes made)
(139 real changes made)
(100 real changes made)
(81 real changes made)
(466 real changes made)
(691 real changes made)
(357 real changes made)
(509 real changes made)
(126 real changes made)
(112 real changes made)
(78 real changes made)

.         label var out_ideo_7 "Perceived Liberalness (0-1)"

.         label var out_ideo_econ "Perceived Liberalness, Economic Issues"

.         label var out_ideo_soc "Perceived Liberalness, Social Issues"

.         
.         
.         // 1 low priority, 3 high priority
.         foreach var in tax job health enviro abort crim sj {
  2.                 gen out_priority_`var' = 0 if cattr_priority_`var' == "Low priority"
  3.                 replace out_priority_`var' = 0.5 if cattr_priority_`var' == "Moderate priority"
  4.                 replace out_priority_`var' = 1 if cattr_priority_`var' == "High priority"
  5.         }
(1,998 missing values generated)
(907 real changes made)
(859 real changes made)
(1,887 missing values generated)
(920 real changes made)
(734 real changes made)
(2,122 missing values generated)
(796 real changes made)
(1,097 real changes made)
(1,928 missing values generated)
(883 real changes made)
(814 real changes made)
(1,901 missing values generated)
(808 real changes made)
(858 real changes made)
(1,839 missing values generated)
(979 real changes made)
(631 real changes made)
(2,139 missing values generated)
(926 real changes made)
(983 real changes made)

.         
.         // 1 very unfair, 7 very fair
.         foreach var in white black asian hispanic gop dem men women {
  2.                 gen out_fair_`var' = 0 if cattr_fair_`var' == "Very Unfair"
  3.                 replace out_fair_`var' = 0.1667 if cattr_fair_`var' == "Unfair"
  4.                 replace out_fair_`var' = 0.3334 if cattr_fair_`var' == "Somewhat Unfair"
  5.                 replace out_fair_`var' = 0.5 if cattr_fair_`var' == "Neutral"
  6.                 replace out_fair_`var' = 0.6667 if cattr_fair_`var' == "Somewhat Fair"
  7.                 replace out_fair_`var' = 0.8334 if cattr_fair_`var' == "Fair"
  8.                 replace out_fair_`var' = 1 if cattr_fair_`var' == "Very Fair"
  9.         }
(2,255 missing values generated)
(166 real changes made)
(275 real changes made)
(637 real changes made)
(273 real changes made)
(393 real changes made)
(289 real changes made)
(2,308 missing values generated)
(107 real changes made)
(211 real changes made)
(535 real changes made)
(286 real changes made)
(457 real changes made)
(489 real changes made)
(2,315 missing values generated)
(135 real changes made)
(247 real changes made)
(740 real changes made)
(340 real changes made)
(408 real changes made)
(221 real changes made)
(2,309 missing values generated)
(132 real changes made)
(223 real changes made)
(653 real changes made)
(341 real changes made)
(448 real changes made)
(290 real changes made)
(2,128 missing values generated)
(255 real changes made)
(349 real changes made)
(651 real changes made)
(217 real changes made)
(229 real changes made)
(199 real changes made)
(2,359 missing values generated)
(93 real changes made)
(164 real changes made)
(543 real changes made)
(293 real changes made)
(529 real changes made)
(511 real changes made)
(2,318 missing values generated)
(146 real changes made)
(268 real changes made)
(716 real changes made)
(298 real changes made)
(422 real changes made)
(245 real changes made)
(2,320 missing values generated)
(132 real changes made)
(202 real changes made)
(598 real changes made)
(339 real changes made)
(474 real changes made)
(351 real changes made)

.         
. // Inference on policy position, 1 liberal, 3 conservative
.         gen out_policy_tanf = 1 if cattr_policy_tanf == "Remove"
(1,454 missing values generated)

.         replace out_policy_tanf = 0.5 if cattr_policy_tanf == "Keep"
(932 real changes made)

.         replace out_policy_tanf = 0 if cattr_policy_tanf == "Reduce"
(226 real changes made)

.         label var out_policy_tanf "Inferred Policy Liberalness, TANF"

.         
.         gen out_policy_minwage = 1 if strpos(cattr_policy_minwage, "$15.00") != 0
(1,499 missing values generated)

.         replace out_policy_minwage = 0.5 if strpos(cattr_policy_minwage, "$10.00") != 0
(799 real changes made)

.         replace out_policy_minwage = 0 if strpos(cattr_policy_minwage, "$7.25") != 0
(403 real changes made)

.         label var out_policy_minwage "Inferred Policy Liberalness, Min. Wage"

.         
.         gen out_policy_repar = 1 if cattr_policy_repar == "Cash"
(1,782 missing values generated)

.         replace out_policy_repar = 0.5 if cattr_policy_repar == "Preferential treatment"
(855 real changes made)

.         replace out_policy_repar = 0 if cattr_policy_repar == "No benefits"
(628 real changes made)

.         label var out_policy_repar "Inferred Policy Liberalness, Reparations"

. 
. // Racial Resentment
.         forvalues x = 1/4 {
  2.                 gen rr_`x' = .
  3.                 replace rr_`x' = 0 if sr`x' == "Disagree strongly"
  4.                 replace rr_`x' = 0.25 if sr`x' == "Disagree somewhat"
  5.                 replace rr_`x' = 0.5 if sr`x' == "Neither agree nor disagree"
  6.                 replace rr_`x' = 0.75 if sr`x' == "Agree somewhat"
  7.                 replace rr_`x' = 1 if sr`x' == "Agree strongly"
  8.         
.         }
(2,467 missing values generated)
(198 real changes made)
(249 real changes made)
(554 real changes made)
(577 real changes made)
(566 real changes made)
(2,467 missing values generated)
(351 real changes made)
(293 real changes made)
(471 real changes made)
(565 real changes made)
(464 real changes made)
(2,467 missing values generated)
(319 real changes made)
(314 real changes made)
(573 real changes made)
(487 real changes made)
(451 real changes made)
(2,467 missing values generated)
(328 real changes made)
(327 real changes made)
(574 real changes made)
(476 real changes made)
(438 real changes made)

.         // Agreement = racially resentful, sr1, s4 | Disagreement = racially resentful, sr2, s3
.         // recode to make high values/agreement mean racially resentful
.         recode rr_2 (0=1) (0.25=0.75) (0.5=0.5) (0.75=0.25) (1=0) 
(1,673 changes made to rr_2)

.         recode rr_3 (0=1) (0.25=0.75) (0.5=0.5) (0.75=0.25) (1=0) 
(1,571 changes made to rr_3)

.         egen resent_scale = rowmean(rr_*)
(322 missing values generated)

.         
.         // Generate binary based on party-mean
.         gen resent_binary = .
(2,467 missing values generated)

.         foreach p in dem gop ind {
  2.                 qui summ resent_scale if r_`p' == 1
  3.                 loc rr = r(mean)
  4.                 replace resent_binary = resent_scale > `rr' if r_`p' == 1
  5.         
.                 // Check
.                 summ resent_scale if r_`p'==1 & resent_binary == 1, d
  6.                 summ resent_scale if r_`p'==1 & resent_binary == 0, d
  7.                 summ resent_scale if r_`p'==1, d
  8.         }
(1,106 real changes made)

                        resent_scale
-------------------------------------------------------------
      Percentiles      Smallest
 1%        .4375          .4375
 5%        .4375          .4375
10%        .4375          .4375       Obs                 548
25%           .5          .4375       Sum of wgt.         548

50%        .5625                      Mean           .5904425
                        Largest       Std. dev.       .148246
75%         .625              1
90%        .8125              1       Variance       .0219769
95%        .9375              1       Skewness       1.329296
99%            1              1       Kurtosis       4.066412

                        resent_scale
-------------------------------------------------------------
      Percentiles      Smallest
 1%            0              0
 5%            0              0
10%            0              0       Obs                 429
25%        .0625              0       Sum of wgt.         429

50%        .1875                      Mean           .1870629
                        Largest       Std. dev.       .131163
75%        .3125           .375
90%         .375           .375       Variance       .0172037
95%         .375           .375       Skewness      -.0727509
99%         .375           .375       Kurtosis       1.707285

                        resent_scale
-------------------------------------------------------------
      Percentiles      Smallest
 1%            0              0
 5%            0              0
10%        .0625              0       Obs                 977
25%          .25              0       Sum of wgt.         977

50%        .4375                      Mean           .4133188
                        Largest       Std. dev.      .2449032
75%        .5625              1
90%        .6875              1       Variance       .0599776
95%         .875              1       Skewness       .1230257
99%            1              1       Kurtosis       2.627766
(993 real changes made)

                        resent_scale
-------------------------------------------------------------
      Percentiles      Smallest
 1%         .625           .625
 5%         .625           .625
10%         .625           .625       Obs                 430
25%        .6875           .625       Sum of wgt.         430

50%        .8125                      Mean           .8114341
                        Largest       Std. dev.      .1372998
75%        .9375              1
90%            1              1       Variance       .0188512
95%            1              1       Skewness       .0484773
99%            1              1       Kurtosis       1.571641

                        resent_scale
-------------------------------------------------------------
      Percentiles      Smallest
 1%            0              0
 5%        .1875              0
10%          .25              0       Obs                 449
25%         .375              0       Sum of wgt.         449

50%           .5                      Mean           .4461303
                        Largest       Std. dev.       .115857
75%           .5          .5625
90%        .5625          .5625       Variance       .0134228
95%        .5625          .5625       Skewness      -1.593723
99%        .5625          .5625       Kurtosis       5.580205

                        resent_scale
-------------------------------------------------------------
      Percentiles      Smallest
 1%        .0625              0
 5%          .25              0
10%         .375              0       Obs                 879
25%           .5              0       Sum of wgt.         879

50%        .5625                      Mean           .6248341
                        Largest       Std. dev.      .2223602
75%        .8125              1
90%            1              1       Variance        .049444
95%            1              1       Skewness       .0496957
99%            1              1       Kurtosis       2.491787
(230 real changes made)

                        resent_scale
-------------------------------------------------------------
      Percentiles      Smallest
 1%        .5625          .5625
 5%        .5625          .5625
10%        .5625          .5625       Obs                  64
25%         .625          .5625       Sum of wgt.          64

50%       .71875                      Mean           .7356771
                        Largest       Std. dev.      .1335726
75%        .8125              1
90%        .9375              1       Variance       .0178416
95%            1              1       Skewness       .4714215
99%            1              1       Kurtosis        2.17305

                        resent_scale
-------------------------------------------------------------
      Percentiles      Smallest
 1%            0              0
 5%        .0625              0
10%        .1875              0       Obs                 122
25%         .375              0       Sum of wgt.         122

50%           .5                      Mean           .4123975
                        Largest       Std. dev.       .137697
75%           .5             .5
90%           .5             .5       Variance       .0189605
95%           .5             .5       Skewness      -1.661769
99%           .5             .5       Kurtosis       4.839423

                        resent_scale
-------------------------------------------------------------
      Percentiles      Smallest
 1%            0              0
 5%        .1875              0
10%          .25              0       Obs                 186
25%        .4375              0       Sum of wgt.         186

50%           .5                      Mean           .5236335
                        Largest       Std. dev.      .2054053
75%         .625              1
90%        .8125              1       Variance       .0421913
95%         .875              1       Skewness      -.0380866
99%            1              1       Kurtosis       3.558199

.         
. /* 
>         Overt Racism
>         overt_lazy, Hardworking (1) - Lazy (7) 
>         overt_unintel, Intelligent (1) - Unintelligent (7)
>         ---- peaceful and trust need to be inverted
>         overt_peaceful, Violent (1) - Peaceful (7)
>         overt_trust, Untrustworthy (1) - Trustworthy (7)
> */
.         foreach y in lazy unintel peaceful trust {
  2.         forvalues x = 1/4{
  3.                 cap drop temp
  4.                 gen temp = real(overt_`y'_`x')
  5.                 drop overt_`y'_`x'
  6.                 rename temp overt_`y'_`x'
  7.         }
  8.         }
(332 missing values generated)
(330 missing values generated)
(335 missing values generated)
(333 missing values generated)
(337 missing values generated)
(335 missing values generated)
(335 missing values generated)
(337 missing values generated)
(329 missing values generated)
(332 missing values generated)
(332 missing values generated)
(335 missing values generated)
(329 missing values generated)
(336 missing values generated)
(330 missing values generated)
(335 missing values generated)

.         // Black - White, if >0 then black rated more negatively
.         gen overt_diff_lazy = overt_lazy_2 - overt_lazy_1
(334 missing values generated)

.         gen overt_diff_unintel = overt_unintel_2 - overt_unintel_1
(341 missing values generated)

.         gen overt_diff_peace = overt_peaceful_1 - overt_peaceful_2 // >0 means white rated more positive
> ly
(333 missing values generated)

.         gen overt_diff_trust = overt_trust_1 - overt_trust_2
(338 missing values generated)

.         
.         egen overt_scale = rowmean(overt_diff*)
(318 missing values generated)

.         // Generate binary based on party-mean
.         gen overt_binary = .
(2,467 missing values generated)

.         foreach p in dem gop ind {
  2.                 qui summ overt_scale if r_`p' == 1
  3.                 loc rr = r(mean)
  4.                 replace overt_binary = overt_scale > `rr' if r_`p' == 1
  5.         
.                 // Check
.                 summ overt_scale if r_`p'==1 & overt_binary == 1, d
  6.                 summ overt_scale if r_`p'==1 & overt_binary == 0, d
  7.                 summ overt_scale if r_`p'==1, d
  8.         }
(1,106 real changes made)

                         overt_scale
-------------------------------------------------------------
      Percentiles      Smallest
 1%    -.1250001      -.1250001
 5%        -.075      -.1250001
10%         -.05      -.1250001       Obs                 646
25%            0      -.1250001       Sum of wgt.         646

50%     .1125001                      Mean           .5351651
                        Largest       Std. dev.      .9132908
75%         .675           5.25
90%         1.75           5.35       Variance          .8341
95%         2.55           5.35       Skewness       2.407783
99%          4.2           5.45       Kurtosis        9.59329

                         overt_scale
-------------------------------------------------------------
      Percentiles      Smallest
 1%           -6             -6
 5%         -5.3             -6
10%    -3.829167             -6       Obs                 340
25%      -1.9875             -6       Sum of wgt.         340

50%        -.775                      Mean          -1.435784
                        Largest       Std. dev.      1.515905
75%    -.3749999           -.15
90%       -.2375           -.15       Variance       2.297968
95%        -.175      -.1499999       Skewness      -1.568737
99%         -.15      -.1499999       Kurtosis       4.559523

                         overt_scale
-------------------------------------------------------------
      Percentiles      Smallest
 1%        -5.55             -6
 5%        -2.95             -6
10%       -1.675             -6       Obs                 986
25%    -.3999999             -6       Sum of wgt.         986

50%            0                      Mean          -.1444726
                        Largest       Std. dev.      1.488481
75%     .3249998           5.25
90%         1.25           5.35       Variance       2.215577
95%        2.125           5.35       Skewness      -.9603167
99%         3.65           5.45       Kurtosis       7.364637
(993 real changes made)

                         overt_scale
-------------------------------------------------------------
      Percentiles      Smallest
 1%     .4999999           .475
 5%         .525           .475
10%     .6250001           .475       Obs                 311
25%     .8750001       .4999999       Sum of wgt.         311

50%         1.45                      Mean            1.76605
                        Largest       Std. dev.      1.156124
75%        2.325          5.025
90%        3.525            5.9       Variance       1.336623
95%     4.166667            5.9       Skewness       1.249677
99%        5.025          5.975       Kurtosis        4.15982

                         overt_scale
-------------------------------------------------------------
      Percentiles      Smallest
 1%       -3.375             -6
 5%         -1.8          -5.15
10%        -.925          -4.15       Obs                 565
25%    -.2750002         -3.875       Sum of wgt.         565

50%    -2.98e-08                      Mean          -.2452802
                        Largest       Std. dev.       .722663
75%         .075           .425
90%         .275           .425       Variance       .5222418
95%          .35       .4499999       Skewness      -3.400254
99%         .425            .45       Kurtosis       18.68685

                         overt_scale
-------------------------------------------------------------
      Percentiles      Smallest
 1%       -3.025             -6
 5%        -1.15          -5.15
10%        -.575          -4.15       Obs                 876
25%          -.1         -3.875       Sum of wgt.         876

50%     .1249998                      Mean           .4687881
                        Largest       Std. dev.      1.318166
75%     .9375001          5.025
90%        2.175            5.9       Variance       1.737561
95%        3.075            5.9       Skewness       .6637239
99%        4.575          5.975       Kurtosis       6.232341
(230 real changes made)

                         overt_scale
-------------------------------------------------------------
      Percentiles      Smallest
 1%         .175           .175
 5%     .1999999       .1750001
10%         .225       .1999999       Obs                  64
25%        .3625       .1999999       Sum of wgt.          64

50%         .725                      Mean           1.352083
                        Largest       Std. dev.      1.337854
75%       2.0375          4.025
90%          3.4          4.375       Variance       1.789855
95%        4.025          5.225       Skewness       1.343861
99%        5.475          5.475       Kurtosis       3.960654

                         overt_scale
-------------------------------------------------------------
      Percentiles      Smallest
 1%       -4.625             -6
 5%        -2.55         -4.625
10%        -1.65          -3.65       Obs                 120
25%    -.4374999          -2.75       Sum of wgt.         120

50%        -.025                      Mean          -.4666667
                        Largest       Std. dev.      .9783386
75%            0            .15
90%        .0875            .15       Variance       .9571464
95%         .125            .15       Skewness      -2.998597
99%          .15            .15       Kurtosis       13.64553

                         overt_scale
-------------------------------------------------------------
      Percentiles      Smallest
 1%       -4.625             -6
 5%       -2.075         -4.625
10%       -1.075          -3.65       Obs                 184
25%        -.125          -2.75       Sum of wgt.         184

50%            0                      Mean            .165942
                        Largest       Std. dev.      1.411754
75%         .425          4.025
90%          1.6          4.375       Variance        1.99305
95%         3.05          5.225       Skewness       .2529783
99%        5.225          5.475       Kurtosis       7.510271

. 
.         
.         keep r_* dem_* cand_* has_race out_* rr_* resent_* overt_diff* overt_scale overt_binary cattr_* 
> ///
>                 hhi_* male female edu_* reg_*

.         
.         save data_study_1.dta, replace
(file data_study_1.dta not found)
file data_study_1.dta saved

. 
.         
. /*-------------------------------------------
>         Study 2
> ---------------------------------------------*/
. 
. 
.         insheet using study_2_raw.csv, comma name clear
(179 vars, 1,858 obs)

. 
.         // Drop people who failed attention check
.                 keep if acq_pass == "1" | acq_identity == "Because he left his ID"
(411 observations deleted)

.                 
.         // Qualtrics demographics
.                 gen r_age = 2021 - real(dem_birth)
(3 missing values generated)

.                 
.                 // Respondent Race
.                 gen r_white = dem_race == "White"

.                 gen r_black = dem_race == "Black or African American"

.                 gen r_asian = dem_race == "Asian"

.                 gen r_hispanic = dem_race == "Hispanic or Latino"

.                 gen r_other = missing(r_white) & missing(r_black) & missing(r_asian) & missing(r_hispani
> c)

.                 
.                 // Party
.                 gen r_dem = dem_pid == "Democrat"

.                 gen r_gop = dem_pid == "Republican"

.                 gen r_ind = dem_pid == "Independent"

.                 
.                 label var r_dem "Respondent PID, Democrats (Incl. Leaners)"

.                 label var r_ind "Respondent PID, Pure Independents"

.                 label var r_gop "Respondent PID, Republicans (Incl. Leaners)"

.                 label var dem_pid "Respondent PID from Qualtrics"

. 
.         keep r_* cattr* cand* 

. 
.         foreach var of varlist cattr_fair_* {
  2.                 di "`var'"
  3.                 loc n = real(substr("`var'", -1, 1))
  4.                 if `n' == . rename `var' `var'__1
  5.                 else {
  6.                         loc n2 = `n'+1
  7.                         loc varname = subinstr("`var'", "_`n'", "", .)
  8.                         rename `var' `varname'__`n2'
  9.                 }
 10.         }
cattr_fair_whites
cattr_fair_blacks
cattr_fair_asians
cattr_fair_hispanics
cattr_fair_gop
cattr_fair_dem
cattr_fair_men
cattr_fair_women
cattr_fair_whites_1
cattr_fair_blacks_1
cattr_fair_asians_1
cattr_fair_hispanics_1
cattr_fair_gop_1
cattr_fair_dem_1
cattr_fair_men_1
cattr_fair_women_1
cattr_fair_whites_2
cattr_fair_blacks_2
cattr_fair_asians_2
cattr_fair_hispanics_2
cattr_fair_gop_2
cattr_fair_dem_2
cattr_fair_men_2
cattr_fair_women_2
cattr_fair_whites_3
cattr_fair_blacks_3
cattr_fair_asians_3
cattr_fair_hispanics_3
cattr_fair_gop_3
cattr_fair_dem_3
cattr_fair_men_3
cattr_fair_women_3
cattr_fair_whites_4
cattr_fair_blacks_4
cattr_fair_asians_4
cattr_fair_hispanics_4
cattr_fair_gop_4
cattr_fair_dem_4
cattr_fair_men_4
cattr_fair_women_4

.         foreach var of varlist cattr_fair_* {
  2.                 loc x = subinstr("`var'", "__", "_", .)
  3.                 rename `var' `x'
  4.         }

. 
.         // I probably could have done a reshape first, but it is what it is.
.         forvalues n = 1/5 {
  2.                 // Outcomes
.                 // perceived candidate ideology 7pts
.                 gen out_ideo_`n' = 1 if cand`n'_ideo == "Extremely Liberal"
  3.                 replace out_ideo_`n' = 0.8334 if cand`n'_ideo == "Liberal"
  4.                 replace out_ideo_`n' = 0.6667 if cand`n'_ideo == "Slightly Liberal"
  5.                 replace out_ideo_`n' = 0.5 if cand`n'_ideo == "Moderate/Middle of the road"
  6.                 replace out_ideo_`n' = 0.3334 if cand`n'_ideo == "Slightly Conservative"
  7.                 replace out_ideo_`n' = 0.1667 if cand`n'_ideo == "Conservative"
  8.                 replace out_ideo_`n' = 0 if cand`n'_ideo == "Extremely Conservative"
  9.                 
.                 // vote
.                 gen out_vote_`n' = 1 if cand`n'_vote == "Very likely"
 10.                 replace out_vote_`n' = 0.75 if cand`n'_vote == "Somewhat likely"
 11.                 replace out_vote_`n' = 0.5 if cand`n'_vote == "Equally likely or unlikely"
 12.                 replace out_vote_`n' = 0.25 if cand`n'_vote == "Somewhat unlikely"
 13.                 replace out_vote_`n' = 0 if cand`n'_vote == "Very unlikely"
 14.                 
.                 // 1 very unfair, 7 very fair
.                 foreach var in whites blacks asians hispanics gop dem men women {
 15.                         gen out_fair_`var'_`n' = 0 if cattr_fair_`var'_`n' == "None at all"
 16.                         replace out_fair_`var'_`n' = 0.25 if cattr_fair_`var'_`n' == "A littlebit"
 17.                         replace out_fair_`var'_`n' = 0.5 if cattr_fair_`var'_`n' == "Somewhat"
 18.                         replace out_fair_`var'_`n' = 0.75 if cattr_fair_`var'_`n' == "A moderateamoun
> t"
 19.                         replace out_fair_`var'_`n' = 1 if cattr_fair_`var'_`n' == "A greatdeal"
 20.                 }
 21.                 
.         // Candidate Profile Attributes
.         foreach var of varlist cattr`n'_* {
 22.                 loc name = subinstr("`var'", "`n'_", "_", .)
 23.                 rename `var' `name'_`n'
 24.         }
 25. 
. }
(1,186 missing values generated)
(430 real changes made)
(271 real changes made)
(333 real changes made)
(71 real changes made)
(51 real changes made)
(28 real changes made)
(1,275 missing values generated)
(318 real changes made)
(388 real changes made)
(210 real changes made)
(357 real changes made)
(1,236 missing values generated)
(310 real changes made)
(485 real changes made)
(272 real changes made)
(169 real changes made)
(1,336 missing values generated)
(236 real changes made)
(455 real changes made)
(370 real changes made)
(275 real changes made)
(1,282 missing values generated)
(283 real changes made)
(527 real changes made)
(309 real changes made)
(163 real changes made)
(1,300 missing values generated)
(264 real changes made)
(480 real changes made)
(362 real changes made)
(194 real changes made)
(1,007 missing values generated)
(381 real changes made)
(359 real changes made)
(176 real changes made)
(91 real changes made)
(1,377 missing values generated)
(171 real changes made)
(348 real changes made)
(392 real changes made)
(466 real changes made)
(1,324 missing values generated)
(244 real changes made)
(588 real changes made)
(347 real changes made)
(145 real changes made)
(1,363 missing values generated)
(195 real changes made)
(525 real changes made)
(386 real changes made)
(257 real changes made)
(1,198 missing values generated)
(429 real changes made)
(271 real changes made)
(325 real changes made)
(97 real changes made)
(52 real changes made)
(23 real changes made)
(1,281 missing values generated)
(314 real changes made)
(390 real changes made)
(244 real changes made)
(331 real changes made)
(1,246 missing values generated)
(327 real changes made)
(456 real changes made)
(290 real changes made)
(173 real changes made)
(1,349 missing values generated)
(226 real changes made)
(489 real changes made)
(383 real changes made)
(251 real changes made)
(1,326 missing values generated)
(304 real changes made)
(527 real changes made)
(342 real changes made)
(153 real changes made)
(1,341 missing values generated)
(263 real changes made)
(516 real changes made)
(373 real changes made)
(189 real changes made)
(1,029 missing values generated)
(376 real changes made)
(382 real changes made)
(191 real changes made)
(78 real changes made)
(1,380 missing values generated)
(134 real changes made)
(372 real changes made)
(457 real changes made)
(417 real changes made)
(1,343 missing values generated)
(197 real changes made)
(604 real changes made)
(390 real changes made)
(152 real changes made)
(1,372 missing values generated)
(172 real changes made)
(535 real changes made)
(416 real changes made)
(249 real changes made)
(1,173 missing values generated)
(408 real changes made)
(250 real changes made)
(325 real changes made)
(100 real changes made)
(63 real changes made)
(26 real changes made)
(1,285 missing values generated)
(305 real changes made)
(400 real changes made)
(227 real changes made)
(352 real changes made)
(1,245 missing values generated)
(316 real changes made)
(501 real changes made)
(268 real changes made)
(159 real changes made)
(1,350 missing values generated)
(241 real changes made)
(491 real changes made)
(396 real changes made)
(221 real changes made)
(1,306 missing values generated)
(285 real changes made)
(513 real changes made)
(339 real changes made)
(168 real changes made)
(1,328 missing values generated)
(282 real changes made)
(508 real changes made)
(358 real changes made)
(179 real changes made)
(1,049 missing values generated)
(386 real changes made)
(385 real changes made)
(192 real changes made)
(85 real changes made)
(1,391 missing values generated)
(156 real changes made)
(415 real changes made)
(413 real changes made)
(406 real changes made)
(1,333 missing values generated)
(255 real changes made)
(577 real changes made)
(344 real changes made)
(155 real changes made)
(1,380 missing values generated)
(180 real changes made)
(519 real changes made)
(439 real changes made)
(240 real changes made)
(1,167 missing values generated)
(389 real changes made)
(250 real changes made)
(357 real changes made)
(96 real changes made)
(50 real changes made)
(24 real changes made)
(1,273 missing values generated)
(310 real changes made)
(431 real changes made)
(202 real changes made)
(326 real changes made)
(1,252 missing values generated)
(318 real changes made)
(460 real changes made)
(305 real changes made)
(168 real changes made)
(1,356 missing values generated)
(245 real changes made)
(475 real changes made)
(391 real changes made)
(244 real changes made)
(1,337 missing values generated)
(293 real changes made)
(501 real changes made)
(367 real changes made)
(175 real changes made)
(1,343 missing values generated)
(264 real changes made)
(508 real changes made)
(386 real changes made)
(183 real changes made)
(1,069 missing values generated)
(388 real changes made)
(408 real changes made)
(187 real changes made)
(85 real changes made)
(1,371 missing values generated)
(135 real changes made)
(386 real changes made)
(460 real changes made)
(389 real changes made)
(1,338 missing values generated)
(204 real changes made)
(571 real changes made)
(400 real changes made)
(162 real changes made)
(1,360 missing values generated)
(171 real changes made)
(516 real changes made)
(433 real changes made)
(238 real changes made)
(1,168 missing values generated)
(388 real changes made)
(275 real changes made)
(326 real changes made)
(98 real changes made)
(54 real changes made)
(27 real changes made)
(1,293 missing values generated)
(321 real changes made)
(407 real changes made)
(230 real changes made)
(333 real changes made)
(1,266 missing values generated)
(323 real changes made)
(465 real changes made)
(301 real changes made)
(177 real changes made)
(1,355 missing values generated)
(245 real changes made)
(478 real changes made)
(403 real changes made)
(229 real changes made)
(1,323 missing values generated)
(287 real changes made)
(539 real changes made)
(346 real changes made)
(151 real changes made)
(1,336 missing values generated)
(248 real changes made)
(531 real changes made)
(365 real changes made)
(191 real changes made)
(1,064 missing values generated)
(409 real changes made)
(373 real changes made)
(191 real changes made)
(89 real changes made)
(1,383 missing values generated)
(142 real changes made)
(406 real changes made)
(435 real changes made)
(398 real changes made)
(1,345 missing values generated)
(239 real changes made)
(554 real changes made)
(387 real changes made)
(164 real changes made)
(1,367 missing values generated)
(165 real changes made)
(524 real changes made)
(432 real changes made)
(245 real changes made)

.         
.         drop cattr_fair* cand*

.         
.         reshape long out_ideo_ out_vote_ out_fair_whites_ out_fair_blacks_ ///
>                 out_fair_asians_ out_fair_hispanics_ out_fair_gop_ out_fair_dem_ ///
>                 out_fair_men_ out_fair_women_ cattr_age_ cattr_sex_ cattr_race_ ///
>                 cattr_exp_ cattr_nrp1_ cattr_nrp2_ cattr_rp_ cattr_policya_ ///
>                 cattr_policyb_ cattr_policyc_ cattr_biden_ cattr_white_ ///
>                 cattr_black_ cattr_hispa_ cattr_asian_ cattr_other_, i(r_*) j(cand) s
(j = 1 2 3 4 5)

Data                               Wide   ->   Long
-----------------------------------------------------------------------------
Number of observations            1,447   ->   7,235       
Number of variables                 140   ->   37          
j variable (5 values)                     ->   cand
xij variables:
   out_ideo_1 out_ideo_2 ... out_ideo_5   ->   out_ideo_
   out_vote_1 out_vote_2 ... out_vote_5   ->   out_vote_
out_fair_whites_1 out_fair_whites_2 ... out_fair_whites_5->out_fair_whites_
out_fair_blacks_1 out_fair_blacks_2 ... out_fair_blacks_5->out_fair_blacks_
out_fair_asians_1 out_fair_asians_2 ... out_fair_asians_5->out_fair_asians_
out_fair_hispanics_1 out_fair_hispanics_2 ... out_fair_hispanics_5->out_fair_hispanics_
out_fair_gop_1 out_fair_gop_2 ... out_fair_gop_5->out_fair_gop_
out_fair_dem_1 out_fair_dem_2 ... out_fair_dem_5->out_fair_dem_
out_fair_men_1 out_fair_men_2 ... out_fair_men_5->out_fair_men_
out_fair_women_1 out_fair_women_2 ... out_fair_women_5->out_fair_women_
cattr_age_1 cattr_age_2 ... cattr_age_5   ->   cattr_age_
cattr_sex_1 cattr_sex_2 ... cattr_sex_5   ->   cattr_sex_
cattr_race_1 cattr_race_2 ... cattr_race_5->   cattr_race_
cattr_exp_1 cattr_exp_2 ... cattr_exp_5   ->   cattr_exp_
cattr_nrp1_1 cattr_nrp1_2 ... cattr_nrp1_5->   cattr_nrp1_
cattr_nrp2_1 cattr_nrp2_2 ... cattr_nrp2_5->   cattr_nrp2_
   cattr_rp_1 cattr_rp_2 ... cattr_rp_5   ->   cattr_rp_
cattr_policya_1 cattr_policya_2 ... cattr_policya_5->cattr_policya_
cattr_policyb_1 cattr_policyb_2 ... cattr_policyb_5->cattr_policyb_
cattr_policyc_1 cattr_policyc_2 ... cattr_policyc_5->cattr_policyc_
cattr_biden_1 cattr_biden_2 ... cattr_biden_5->cattr_biden_
cattr_white_1 cattr_white_2 ... cattr_white_5->cattr_white_
cattr_black_1 cattr_black_2 ... cattr_black_5->cattr_black_
cattr_hispa_1 cattr_hispa_2 ... cattr_hispa_5->cattr_hispa_
cattr_asian_1 cattr_asian_2 ... cattr_asian_5->cattr_asian_
cattr_other_1 cattr_other_2 ... cattr_other_5->cattr_other_
-----------------------------------------------------------------------------

.                 
.         foreach var of varlist cattr_* out_* {
  2.                 loc l = strlen("`var'") - 1
  3.                 loc x = substr("`var'", 1, `l')
  4.                 rename `var' `x'
  5.         }

.         
.         
. // Clean Candidate Profile Attributes
. 
.         gen cand_age = real(cattr_age)

.         gen cand_black = cattr_race == "Black"

.         gen cand_white = cattr_race == "White"

.         gen cand_asian = cattr_race == "Asian"

.         gen cand_hispa = cattr_race == "Hispanic"

.         gen cand_female = cattr_sex == "woman"

.         gen cand_male = cattr_sex == "man"

.         
.         gen cand_exp_teach = strpos(cattr_exp, "high school teacher") != 0

.         gen cand_exp_council = strpos(cattr_exp, "city councilor") != 0

.         gen cand_exp_lawyer = strpos(cattr_exp, "local attorney") != 0

.         gen cand_exp_business = strpos(cattr_exp, "business owner") != 0

.         gen cand_exp_newcomer = strpos(cattr_exp, "political newcomer") != 0

.         
.         forvalues v = 51(2)59 {
  2.                 gen cand_biden_p`v' = cattr_biden == "`v'"
  3.                 label var cand_biden_p`v' "Vote Share: `v'%"
  4.         }

.         
.         // Candidate district
.         gen cand_dist1 = cattr_white == "23"

.         gen cand_dist2 = cattr_white == "21"

.         gen cand_dist3 = cattr_white == "28"

.         gen cand_dist4 = cattr_white == "53"

.         gen cand_dist5 = cattr_white == "55"

.         gen cand_dist6 = cattr_white == "59"

.         gen cand_dist7 = cattr_white == "63"

.         label var cand_dist1 "[23, 20, 21, 31, 5]"

.         label var cand_dist2 "[21, 16, 51, 8, 4]"

.         label var cand_dist3 "[28, 53, 9, 6, 4]"

.         label var cand_dist4 "[53, 23, 12, 7, 5]"

.         label var cand_dist5 "[55, 10, 23, 8, 4]"

.         label var cand_dist6 "[59, 16, 14, 7, 4]"

.         label var cand_dist7 "[63, 8, 13, 11, 5]"

.         
. 
.         label var cand_age "Candidate Age"

.         label var cand_black "Black"

.         label var cand_white "White"

.         label var cand_asian "Asian"

.         label var cand_hispa "Hispanic"

.         label var cand_female "Female"

.         label var cand_male "Male"

.         
.         label var cand_exp_teach "High school teacher"

.         label var cand_exp_council "City councilor"

.         label var cand_exp_lawyer "Local attorney"

.         label var cand_exp_business "Local business owner"

.         label var cand_exp_newcomer "Political newcomer"

. 
.         /* 
>                 Use key phrases to determine issue area.
>                 strpos return 0 if text is not found, so if !=0, then phrase is in variable
>         */
.         loc attr "cand_policy_abort1 cand_policy_abort2 cand_policy_tax1 cand_policy_tax2 cand_policy_he
> alth1"

.         loc attr2 "cand_policy_health2 cand_policy_eco1 cand_policy_eco2 cand_policy_aa1 cand_policy_aa2
>  cand_policy_aa3"

.         
.         foreach var in `attr' `attr2' {
  2.                 gen `var' = 0
  3.         }

.         
.         foreach x in a b c {    
  2.                 replace cand_policy_abort2 = 1 if strpos(cattr_policy`x', "first trimester") != 0
  3.                 replace cand_policy_abort1 = 1 if strpos(cattr_policy`x', "including the third trimes
> ter") != 0
  4.                 
.                 replace cand_policy_tax1 = 1 if strpos(cattr_policy`x', "Increase the tax rate") != 0
  5.                 replace cand_policy_tax2 = 1 if strpos(cattr_policy`x', "Maintain the current tax rat
> e") != 0
  6.                 
.                 replace cand_policy_health1 = 1 if strpos(cattr_policy`x', "Replace private health") != 
> 0
  7.                 replace cand_policy_health2 = 1 if strpos(cattr_policy`x', "Maintain current Obamacar
> e") != 0
  8.                 
.                 replace cand_policy_eco1 = 1 if strpos(cattr_policy`x', "Expand investment in renewable"
> ) != 0
  9.                 replace cand_policy_eco2 = 1 if strpos(cattr_policy`x', "Maintain current patterns") 
> != 0
 10.                 
.                 replace cand_policy_aa1 = 1 if strpos(cattr_policy`x', "Expand affirmative action") != 0
 11.                 replace cand_policy_aa2 = 1 if strpos(cattr_policy`x', "Maintain existing affirmative
>  action") != 0
 12.                 replace cand_policy_aa3 = 1 if strpos(cattr_policy`x', "End affirmative action") != 0
 13.         }
(607 real changes made)
(570 real changes made)
(602 real changes made)
(619 real changes made)
(563 real changes made)
(590 real changes made)
(633 real changes made)
(600 real changes made)
(620 real changes made)
(580 real changes made)
(612 real changes made)
(625 real changes made)
(574 real changes made)
(598 real changes made)
(590 real changes made)
(599 real changes made)
(584 real changes made)
(606 real changes made)
(636 real changes made)
(602 real changes made)
(608 real changes made)
(589 real changes made)
(633 real changes made)
(609 real changes made)
(626 real changes made)
(603 real changes made)
(587 real changes made)
(625 real changes made)
(603 real changes made)
(588 real changes made)
(639 real changes made)
(581 real changes made)
(564 real changes made)

.                         
.                 
.         label var cand_policy_abort1 "Allow abortion, any time"

.         label var cand_policy_abort2 "Allow abortion up to 2nd tri."

.         label var cand_policy_tax1 "Increase tax rate on rich"

.         label var cand_policy_tax2 "Maintain tax rate on rich"

.         label var cand_policy_health1 "Expand health coverage"

.         label var cand_policy_health2 "Maintain health coverage"

.         label var cand_policy_eco1 "Expand investment in energy"

.         label var cand_policy_eco2 "Maintain investment in energy"

.         label var cand_policy_aa1 "Expand affirmative action"

.         label var cand_policy_aa2 "Keep affirmative action as is"

.         label var cand_policy_aa3 "End affirmative action"

.         
.         // Check that each policy type appears only once
.         egen temp_tax = rowtotal(cand_policy_tax*)

.         egen temp_abort = rowtotal(cand_policy_abort*)

.         egen temp_health = rowtotal(cand_policy_health*)

.         egen temp_eco = rowtotal(cand_policy_eco*)

.         egen temp_aa = rowtotal(cand_policy_aa*)

.         codebook temp_*

----------------------------------------------------------------------------------------------------------
temp_tax                                                                                       (unlabeled)
----------------------------------------------------------------------------------------------------------

                  Type: Numeric (float)

                 Range: [0,1]                         Units: 1
         Unique values: 2                         Missing .: 0/7,235

            Tabulation: Freq.  Value
                        3,597  0
                        3,638  1

----------------------------------------------------------------------------------------------------------
temp_abort                                                                                     (unlabeled)
----------------------------------------------------------------------------------------------------------

                  Type: Numeric (float)

                 Range: [0,1]                         Units: 1
         Unique values: 2                         Missing .: 0/7,235

            Tabulation: Freq.  Value
                        3,617  0
                        3,618  1

----------------------------------------------------------------------------------------------------------
temp_health                                                                                    (unlabeled)
----------------------------------------------------------------------------------------------------------

                  Type: Numeric (float)

                 Range: [0,1]                         Units: 1
         Unique values: 2                         Missing .: 0/7,235

            Tabulation: Freq.  Value
                        3,687  0
                        3,548  1

----------------------------------------------------------------------------------------------------------
temp_eco                                                                                       (unlabeled)
----------------------------------------------------------------------------------------------------------

                  Type: Numeric (float)

                 Range: [0,1]                         Units: 1
         Unique values: 2                         Missing .: 0/7,235

            Tabulation: Freq.  Value
                        3,569  0
                        3,666  1

----------------------------------------------------------------------------------------------------------
temp_aa                                                                                        (unlabeled)
----------------------------------------------------------------------------------------------------------

                  Type: Numeric (float)

                 Range: [0,1]                         Units: 1
         Unique values: 2                         Missing .: 0/7,235

            Tabulation: Freq.  Value
                        1,840  0
                        5,395  1

.         drop temp_*

.         
.         gen has_racepolicy = (cand_policy_aa1 == 1) | (cand_policy_aa2 == 1) | (cand_policy_aa3 == 1)

.         label var has_racepolicy "Candidate profile has a racial policy"

. 
.         save data_study_2.dta, replace
(file data_study_2.dta not found)
file data_study_2.dta saved

. 
. 
end of do-file

. do 2_study1_analysis.do

. /*
>         Figure 1. Effect of Candidate Attributes on Perceived Candidate Liberalness
>         Corresponds to Table S1a and Table S1b in Appendix
>         
> */
. 
. 
. use data_study_1.dta, clear

.         
. // Set omitted categories for coefplot
.         gen zero_race = 0

.         label var zero_race "White"

.         gen zero_sex = 0

.         label var zero_sex "Male"

.         gen zero_eco = 0

.         label var zero_eco "Maintain investment in energy"

.         gen zero_aa = 0

.         label var zero_aa "Not shown policy"

. 
.         // Set regression variables
.         loc reg_race "cand_black zero_race"

.         loc reg_sex "cand_female zero_sex"

.         loc reg_issues "cand_policy_abort1 cand_policy_abort2 cand_policy_tax1 cand_policy_tax2"

.         loc reg_issues "`reg_issues' cand_policy_health1 cand_policy_health2 cand_policy_eco1 zero_eco"

.         loc reg_affirm "cand_policy_aa1 cand_policy_aa2 cand_policy_aa3 zero_aa"

.         
. // Interactive Terms for Black Candidate X Affirmative Action
.         gen noracepolicy = cand_policy_aa1 == 0 & cand_policy_aa2 == 0 & cand_policy_aa3 == 0   

.         gen black_aa1 = cand_policy_aa1*cand_black

.         gen black_aa2 = cand_policy_aa2*cand_black

.         gen black_aa3 = cand_policy_aa3*cand_black

.         gen white_aa1 = cand_policy_aa1*cand_white

.         gen white_aa2 = cand_policy_aa2*cand_white

.         gen white_aa3 = cand_policy_aa3*cand_white

.         label var black_aa1 "Black X Expand (race)"

.         label var black_aa2 "Black X Keep as is"

.         label var black_aa3 "Black X Replace (class)"

.         label var white_aa1 "White X Expand (race)"

.         label var white_aa2 "White X Keep as is"

.         label var white_aa3 "White X Replace (class)"

.         label var noracepolicy "Not shown position"

.         
.         loc int "white_aa1 white_aa2 white_aa3 black_aa1 black_aa2 black_aa3"

.         
.         gen out_fair_bwdiff = out_fair_black - out_fair_white
(226 missing values generated)

.         
. //============================================================================== No interaction
. 
.          reg out_ideo_7 cand_black zero_race cand_female zero_sex cand_policy_abort1 ///
>                 cand_policy_abort2 cand_policy_tax1 cand_policy_tax2 ///
>                 cand_policy_health1 cand_policy_health2 cand_policy_eco1 zero_eco ///
>                 cand_policy_aa1 cand_policy_aa2 cand_policy_aa3 zero_aa cand_age, robust
note: zero_race omitted because of collinearity.
note: zero_sex omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: zero_aa omitted because of collinearity.

Linear regression                               Number of obs     =      2,339
                                                F(13, 2325)       =       3.42
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0194
                                                Root MSE          =     .26078

-------------------------------------------------------------------------------------
                    |               Robust
         out_ideo_7 | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
         cand_black |   .0308883   .0108174     2.86   0.004     .0096755    .0521012
          zero_race |          0  (omitted)
        cand_female |   .0035406   .0108202     0.33   0.744    -.0176776    .0247588
           zero_sex |          0  (omitted)
 cand_policy_abort1 |   .0810021   .0174745     4.64   0.000     .0467349    .1152694
 cand_policy_abort2 |   .0380729   .0169359     2.25   0.025     .0048619     .071284
   cand_policy_tax1 |   .0277552    .016437     1.69   0.091    -.0044775    .0599878
   cand_policy_tax2 |  -.0032342   .0167002    -0.19   0.846     -.035983    .0295146
cand_policy_health1 |   .0406081   .0164612     2.47   0.014     .0083279    .0728884
cand_policy_health2 |   .0364301   .0169876     2.14   0.032     .0031178    .0697425
   cand_policy_eco1 |   .0110018   .0151636     0.73   0.468    -.0187338    .0407374
           zero_eco |          0  (omitted)
    cand_policy_aa1 |   .0202985   .0149494     1.36   0.175     -.009017    .0496141
    cand_policy_aa2 |   .0061395   .0157467     0.39   0.697    -.0247396    .0370185
    cand_policy_aa3 |  -.0071819   .0148188    -0.48   0.628    -.0362414    .0218776
            zero_aa |          0  (omitted)
           cand_age |  -.0009518   .0008903    -1.07   0.285    -.0026977     .000794
              _cons |    .649126   .0511456    12.69   0.000     .5488303    .7494218
-------------------------------------------------------------------------------------

. 
.         
.         // Ideology
.         reg out_ideo_7 `reg_race' `reg_sex' `reg_issues' `reg_affirm' cand_age, robust
note: zero_race omitted because of collinearity.
note: zero_sex omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: zero_aa omitted because of collinearity.

Linear regression                               Number of obs     =      2,339
                                                F(13, 2325)       =       3.42
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0194
                                                Root MSE          =     .26078

-------------------------------------------------------------------------------------
                    |               Robust
         out_ideo_7 | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
         cand_black |   .0308883   .0108174     2.86   0.004     .0096755    .0521012
          zero_race |          0  (omitted)
        cand_female |   .0035406   .0108202     0.33   0.744    -.0176776    .0247588
           zero_sex |          0  (omitted)
 cand_policy_abort1 |   .0810021   .0174745     4.64   0.000     .0467349    .1152694
 cand_policy_abort2 |   .0380729   .0169359     2.25   0.025     .0048619     .071284
   cand_policy_tax1 |   .0277552    .016437     1.69   0.091    -.0044775    .0599878
   cand_policy_tax2 |  -.0032342   .0167002    -0.19   0.846     -.035983    .0295146
cand_policy_health1 |   .0406081   .0164612     2.47   0.014     .0083279    .0728884
cand_policy_health2 |   .0364301   .0169876     2.14   0.032     .0031178    .0697425
   cand_policy_eco1 |   .0110018   .0151636     0.73   0.468    -.0187338    .0407374
           zero_eco |          0  (omitted)
    cand_policy_aa1 |   .0202985   .0149494     1.36   0.175     -.009017    .0496141
    cand_policy_aa2 |   .0061395   .0157467     0.39   0.697    -.0247396    .0370185
    cand_policy_aa3 |  -.0071819   .0148188    -0.48   0.628    -.0362414    .0218776
            zero_aa |          0  (omitted)
           cand_age |  -.0009518   .0008903    -1.07   0.285    -.0026977     .000794
              _cons |    .649126   .0511456    12.69   0.000     .5488303    .7494218
-------------------------------------------------------------------------------------

.         eststo ideo

.                 loc b_ideo = string(round(_b[_cons], 0.001), "%9.3f") // store mean values

.         outreg2 using table_s1_fig1results.xls, replace ctitle(Ideology)
table_s1_fig1results.xls
dir : seeout

.         
.         // Issue Priority (social justice)
.         reg out_priority_sj `reg_race' `reg_sex' `reg_issues' `reg_affirm' cand_age, robust
note: zero_race omitted because of collinearity.
note: zero_sex omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: zero_aa omitted because of collinearity.

Linear regression                               Number of obs     =      2,237
                                                F(13, 2223)       =       2.90
                                                Prob > F          =     0.0003
                                                R-squared         =     0.0165
                                                Root MSE          =     .35184

-------------------------------------------------------------------------------------
                    |               Robust
    out_priority_sj | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
         cand_black |   .0501537   .0149099     3.36   0.001      .020915    .0793925
          zero_race |          0  (omitted)
        cand_female |  -.0254878   .0149288    -1.71   0.088    -.0547637     .003788
           zero_sex |          0  (omitted)
 cand_policy_abort1 |   .0033109   .0233739     0.14   0.887    -.0425261    .0491479
 cand_policy_abort2 |   .0106649   .0237467     0.45   0.653    -.0359031    .0572329
   cand_policy_tax1 |   .0253104    .023567     1.07   0.283    -.0209054    .0715261
   cand_policy_tax2 |   .0195874   .0230759     0.85   0.396    -.0256651    .0648399
cand_policy_health1 |   .0131858   .0227727     0.58   0.563    -.0314723    .0578438
cand_policy_health2 |   .0180586   .0242777     0.74   0.457    -.0295507    .0656679
   cand_policy_eco1 |   .0350403   .0212005     1.65   0.099    -.0065346    .0766151
           zero_eco |          0  (omitted)
    cand_policy_aa1 |   .0865824   .0210885     4.11   0.000     .0452271    .1279377
    cand_policy_aa2 |   .0642988   .0216339     2.97   0.003     .0218741    .1067235
    cand_policy_aa3 |   .0615324   .0205488     2.99   0.003     .0212356    .1018291
            zero_aa |          0  (omitted)
           cand_age |   .0014533   .0012263     1.19   0.236    -.0009516    .0038582
              _cons |   .4775369   .0713069     6.70   0.000     .3377019    .6173719
-------------------------------------------------------------------------------------

.         eststo sj

.                 loc b_sj = string(round(_b[_cons], 0.001), "%9.3f")     

.         outreg2 using table_s1_fig1results.xls, append ctitle(Social Justice Priority)
table_s1_fig1results.xls
dir : seeout

.         
.         reg out_fair_bwdiff `reg_race' `reg_sex' `reg_issues' `reg_affirm' cand_age, robust
note: zero_race omitted because of collinearity.
note: zero_sex omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: zero_aa omitted because of collinearity.

Linear regression                               Number of obs     =      2,241
                                                F(13, 2227)       =       5.37
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0304
                                                Root MSE          =     .37922

-------------------------------------------------------------------------------------
                    |               Robust
    out_fair_bwdiff | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
         cand_black |   .0977633   .0160124     6.11   0.000     .0663626     .129164
          zero_race |          0  (omitted)
        cand_female |   .0323967    .016018     2.02   0.043      .000985    .0638084
           zero_sex |          0  (omitted)
 cand_policy_abort1 |   .0092227   .0256115     0.36   0.719    -.0410022    .0594475
 cand_policy_abort2 |   .0016556   .0249533     0.07   0.947    -.0472786    .0505898
   cand_policy_tax1 |   .0157005   .0250456     0.63   0.531    -.0334148    .0648157
   cand_policy_tax2 |   .0295684   .0237303     1.25   0.213    -.0169675    .0761043
cand_policy_health1 |   .0296374   .0239094     1.24   0.215    -.0172496    .0765244
cand_policy_health2 |   .0354464   .0274426     1.29   0.197    -.0183694    .0892622
   cand_policy_eco1 |   .0436711   .0230313     1.90   0.058     -.001494    .0888363
           zero_eco |          0  (omitted)
    cand_policy_aa1 |   .0829266   .0223865     3.70   0.000      .039026    .1268272
    cand_policy_aa2 |    .065673   .0229511     2.86   0.004     .0206651    .1106808
    cand_policy_aa3 |  -.0021573   .0212713    -0.10   0.919    -.0438709    .0395562
            zero_aa |          0  (omitted)
           cand_age |   .0004194   .0013246     0.32   0.752    -.0021782     .003017
              _cons |  -.0824198   .0750958    -1.10   0.273    -.2296848    .0648453
-------------------------------------------------------------------------------------

.         eststo fairness

.                 loc b_fair = string(round(_b[_cons], 0.001), "%9.3f")   

.         outreg2 using table_s1_fig1results.xls, append ctitle(Fairness to Black over Whites)
table_s1_fig1results.xls
dir : seeout

.         
. 
.         coefplot (ideo, label() mc(gs4) ciopts(color(gs4) lw(med))) ///
>                                         , bylabel("{bf:(a) Ideological Liberalness}") || ///
>                          (sj, label() mc(gs4) ciopts(color(gs4) lw(med))) ///
>                                 , bylabel("{bf:(b) Prioritize Social Justice}") || ///
>                          (fairness, label() mc(gs4) ciopts(color(gs4) lw(med))) ///
>                                 , bylabel("{bf:(c) Fairer to Black than White Constituents}") ///
>                         || , drop(_cons cand_age) omitted baselevels ms(c) msize(medsmall) ylabel(,labsi
> ze(vsmall)) ///
>                 xline(0, lc(black)) nokey ///
>                 byopts(row(1) t1title("{bf:`title'}", size(small))) ///
>                 subtitle(, bcolor(white) color(black) size(vsmall)) ///
>                 xtitle("Effects of Candidate Attributes (Scale 0 to 1)", size(vsmall)) ///
>                 legend(order(2 "Democrats" 4 "Republicans") size(vsmall) position(bottom))  ///
>                 xlabel(-0.1(0.05)0.15,labsize(small)) norecycle ///
>                 headings(cand_black = "{bf: Race}" cand_female = "{bf: Sex}" ///
>                         cand_policy_abort1 = "{bf: Abortion}" cand_policy_tax1 = "{bf: Tax Policy}" ///
>                         cand_policy_health1 = "{bf: Health Care}" cand_policy_eco1 = "{bf: Renewable Ene
> rgy}" ///
>                         cand_policy_aa1 = "{bf: Affirmative Actions}", labsize(vsmall)) ///
>                         saving(lucid.gph, replace) 
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(file lucid.gph not found)
file lucid.gph saved

.                 
.         addplot 1: ,note("Mean, Baseline Categories = `b_ideo'", size(vsmall)) norescaling

.         addplot 2: ,note("Mean, Baseline Categories = `b_sj'", size(vsmall)) norescaling                

.         addplot 3: ,note("Mean, Baseline Categories = `b_fair'", size(vsmall)) norescaling              

.         
.         graph display, xsize(4.5) ysize(3.4) margins(vsmall)    

.         graph export figure_1.png, as(png) replace
(file figure_1.png not found)
file figure_1.png saved as PNG format

. 
. /*
>         Figure 2. Effect of Interaction (AA position x candidate race)
>                 - Corresponds to Table S2
>                 
>         Also creates Table S3 (additional issue priority outcomes)
> */
. 
. use data_study_1.dta, clear

. 
. // Set omitted categories
.         gen zero_race = 0

.         label var zero_race "White"

.         gen zero_sex = 0

.         label var zero_sex "Male"

.         gen zero_eco = 0

.         label var zero_eco "Maintain investment in energy"

.         
. // Set regression variables
.         loc reg_race "cand_black zero_race"

.         loc reg_sex "cand_female zero_sex"

.         loc reg_issues "cand_policy_abort1 cand_policy_abort2 cand_policy_tax1 cand_policy_tax2"

.         loc reg_issues "`reg_issues' cand_policy_health1 cand_policy_health2 cand_policy_eco1 zero_eco"

.         loc reg_affirm "cand_policy_aa1 cand_policy_aa2 cand_policy_aa3"

.         
. // Interactive Terms for Black Candidate X Affirmative Action
.         gen noracepolicy = cand_policy_aa1 == 0 & cand_policy_aa2 == 0 & cand_policy_aa3 == 0   

.         gen black_aa1 = cand_policy_aa1*cand_black

.         gen black_aa2 = cand_policy_aa2*cand_black

.         gen black_aa3 = cand_policy_aa3*cand_black

.         gen white_aa1 = cand_policy_aa1*cand_white

.         gen white_aa2 = cand_policy_aa2*cand_white

.         gen white_aa3 = cand_policy_aa3*cand_white

.         gen black_aa0 = noracepolicy*cand_black

.         gen white_aa0 = noracepolicy*cand_white

.         label var black_aa0 "Black X No Position"

.         label var white_aa0 "White X No Position"

.         label var black_aa1 "Black X Expand (race)"

.         label var black_aa2 "Black X Keep as is"

.         label var black_aa3 "Black X Replace (class)"

.         label var white_aa1 "White X Expand (race)"

.         label var white_aa2 "White X Keep as is"

.         label var white_aa3 "White X Replace (class)"

.         replace white_aa0 = 0
(294 real changes made)

.         label var noracepolicy "Not shown position"

.         loc int "white_aa0 white_aa1 white_aa2 white_aa3 black_aa0 black_aa1 black_aa2 black_aa3"

.         
.         gen out_fair_bwdiff = out_fair_black - out_fair_white
(226 missing values generated)

.                 
.                 
. // Run regressions to get estimates using eststo, while also creating appendix tables
.         // Column 1 (Ideological Liberalness)
.         reg out_ideo_7 `reg_sex' `reg_issues' `int' cand_age, robust
note: zero_sex omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      2,339
                                                F(16, 2322)       =       3.08
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0210
                                                Root MSE          =     .26074

-------------------------------------------------------------------------------------
                    |               Robust
         out_ideo_7 | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |   .0042271   .0108417     0.39   0.697    -.0170334    .0254875
           zero_sex |          0  (omitted)
 cand_policy_abort1 |   .0815165    .017496     4.66   0.000     .0472071    .1158259
 cand_policy_abort2 |   .0381148   .0169459     2.25   0.025     .0048842    .0713454
   cand_policy_tax1 |   .0278099   .0164508     1.69   0.091    -.0044499    .0600697
   cand_policy_tax2 |  -.0039468   .0166908    -0.24   0.813    -.0366772    .0287836
cand_policy_health1 |   .0398922   .0164599     2.42   0.015     .0076145    .0721699
cand_policy_health2 |   .0361844   .0170259     2.13   0.034     .0027968    .0695719
   cand_policy_eco1 |    .011355   .0151719     0.75   0.454    -.0183969    .0411069
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          white_aa1 |   .0130188   .0223867     0.58   0.561    -.0308812    .0569188
          white_aa2 |   .0277604   .0227521     1.22   0.223     -.016856    .0723769
          white_aa3 |   .0015667   .0212611     0.07   0.941     -.040126    .0432593
          black_aa0 |   .0417546   .0212423     1.97   0.049     .0000988    .0834104
          black_aa1 |   .0691943   .0210209     3.29   0.001     .0279727    .1104159
          black_aa2 |   .0269197   .0227852     1.18   0.238    -.0177618    .0716012
          black_aa3 |   .0263299   .0217311     1.21   0.226    -.0162845    .0689443
           cand_age |  -.0009288   .0008908    -1.04   0.297    -.0026757     .000818
              _cons |   .6421046   .0523822    12.26   0.000     .5393839    .7448253
-------------------------------------------------------------------------------------

.         eststo ideo

.                 loc b_ideo = string(round(_b[_cons], 0.001), "%9.3f")

.         outreg2 using table_s2_fig2results.xls, replace ctitle(Ideological Liberalness) 
table_s2_fig2results.xls
dir : seeout

.         
.         // Column 2 (SJ priority) + additional outcomes for Table S3
.         loc c = 0

.         d out_priority*, varlist

Variable      Storage   Display    Value
    name         type    format    label      Variable label
----------------------------------------------------------------------------------------------------------
out_priority_~x float   %9.0g                 
out_priority_~b float   %9.0g                 
out_priority_~h float   %9.0g                 
out_priority_~o float   %9.0g                 
out_priority_~t float   %9.0g                 
out_priority_~m float   %9.0g                 
out_priority_sj float   %9.0g                 

.         foreach var in `r(varlist)' {
  2.                 reg `var' `reg_sex' `reg_issues' `int' cand_age , robust
  3.                 eststo r_`var'
  4.                 if `c' == 0 outreg2 using table_s3.xls, replace ctitle(`var')
  5.                 if `c' != 0 outreg2 using table_s3.xls, append ctitle(`var')
  6.                 if "`var'" == "out_priority_sj" {
  7.                         loc b_sj = string(round(_b[_cons], 0.001), "%9.3f")
  8.                         outreg2 using table_s2_fig2results.xls, append ctitle(Social Justice)
  9.                 }
 10.                 loc c = 1
 11.         }
note: zero_sex omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      2,235
                                                F(16, 2218)       =      13.09
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0789
                                                Root MSE          =     .36167

-------------------------------------------------------------------------------------
                    |               Robust
   out_priority_tax | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |  -.0280774   .0153734    -1.83   0.068    -.0582252    .0020704
           zero_sex |          0  (omitted)
 cand_policy_abort1 |  -.0129955   .0239717    -0.54   0.588    -.0600048    .0340138
 cand_policy_abort2 |   -.024277   .0250207    -0.97   0.332    -.0733435    .0247895
   cand_policy_tax1 |   .2483764   .0232638    10.68   0.000     .2027553    .2939975
   cand_policy_tax2 |   .1208549   .0243331     4.97   0.000     .0731368     .168573
cand_policy_health1 |   .0255278    .024034     1.06   0.288    -.0216037    .0726593
cand_policy_health2 |   .0220714    .025285     0.87   0.383    -.0275133    .0716562
   cand_policy_eco1 |   .0307661   .0219634     1.40   0.161    -.0123049     .073837
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          white_aa1 |  -.0216163   .0312474    -0.69   0.489    -.0828936     .039661
          white_aa2 |   -.028682   .0314259    -0.91   0.362    -.0903093    .0329454
          white_aa3 |   .0080121   .0297698     0.27   0.788    -.0503676    .0663917
          black_aa0 |   .0393239   .0297935     1.32   0.187    -.0191021    .0977499
          black_aa1 |  -.0044572   .0304467    -0.15   0.884    -.0641642    .0552497
          black_aa2 |   .0160612    .030589     0.53   0.600    -.0439249    .0760472
          black_aa3 |   .0137147   .0304946     0.45   0.653    -.0460861    .0735156
           cand_age |   .0008316   .0012942     0.64   0.521    -.0017063    .0033696
              _cons |   .4523594   .0756708     5.98   0.000     .3039664    .6007524
-------------------------------------------------------------------------------------
table_s3.xls
dir : seeout
note: zero_sex omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      2,234
                                                F(16, 2217)       =       1.65
                                                Prob > F          =     0.0503
                                                R-squared         =     0.0115
                                                Root MSE          =     .38116

-------------------------------------------------------------------------------------
                    |               Robust
   out_priority_job | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |  -.0274839   .0161762    -1.70   0.089     -.059206    .0042382
           zero_sex |          0  (omitted)
 cand_policy_abort1 |  -.0332835   .0247958    -1.34   0.180     -.081909     .015342
 cand_policy_abort2 |  -.0665715   .0258084    -2.58   0.010    -.1171826   -.0159604
   cand_policy_tax1 |  -.0341033   .0254288    -1.34   0.180      -.08397    .0157634
   cand_policy_tax2 |  -.0185349   .0252583    -0.73   0.463    -.0680672    .0309974
cand_policy_health1 |  -.0245579   .0246288    -1.00   0.319    -.0728557      .02374
cand_policy_health2 |  -.0214812   .0260751    -0.82   0.410    -.0726153     .029653
   cand_policy_eco1 |  -.0346703   .0228106    -1.52   0.129    -.0794027    .0100621
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          white_aa1 |   .0157825   .0329614     0.48   0.632     -.048856     .080421
          white_aa2 |   .0107744   .0328065     0.33   0.743    -.0535604    .0751092
          white_aa3 |   .0174627   .0314811     0.55   0.579    -.0442728    .0791982
          black_aa0 |   .0155386   .0314766     0.49   0.622    -.0461882    .0772654
          black_aa1 |   .0503076    .031856     1.58   0.114    -.0121631    .1127783
          black_aa2 |   .0455371    .031973     1.42   0.155     -.017163    .1082372
          black_aa3 |   .0986806   .0312394     3.16   0.002      .037419    .1599423
           cand_age |  -.0004581   .0013441    -0.34   0.733     -.003094    .0021778
              _cons |   .5966033   .0770343     7.74   0.000     .4455364    .7476703
-------------------------------------------------------------------------------------
table_s3.xls
dir : seeout
note: zero_sex omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      2,238
                                                F(16, 2221)       =      10.18
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0643
                                                Root MSE          =     .35393

-------------------------------------------------------------------------------------
                    |               Robust
out_priority_health | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |  -.0221949   .0149665    -1.48   0.138    -.0515447    .0071549
           zero_sex |          0  (omitted)
 cand_policy_abort1 |   .0363114   .0236448     1.54   0.125    -.0100569    .0826797
 cand_policy_abort2 |   .0133268   .0242781     0.55   0.583    -.0342833    .0609369
   cand_policy_tax1 |  -.0088331   .0238708    -0.37   0.711    -.0556445    .0379784
   cand_policy_tax2 |    .023649   .0234874     1.01   0.314    -.0224106    .0697087
cand_policy_health1 |   .2143274   .0226578     9.46   0.000     .1698947    .2587602
cand_policy_health2 |   .1375189   .0243338     5.65   0.000     .0897995    .1852382
   cand_policy_eco1 |   .0099345   .0217216     0.46   0.647    -.0326623    .0525313
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          white_aa1 |  -.0524183   .0301442    -1.74   0.082     -.111532    .0066955
          white_aa2 |  -.0327992   .0304897    -1.08   0.282    -.0925905    .0269922
          white_aa3 |  -.0735217    .029417    -2.50   0.013    -.1312094   -.0158341
          black_aa0 |  -.0133717   .0283625    -0.47   0.637    -.0689915    .0422481
          black_aa1 |  -.0527321   .0298994    -1.76   0.078    -.1113659    .0059016
          black_aa2 |  -.0493064   .0310579    -1.59   0.113     -.110212    .0115992
          black_aa3 |  -.0131946   .0291396    -0.45   0.651    -.0703383    .0439492
           cand_age |  -.0000533   .0012383    -0.04   0.966    -.0024817    .0023751
              _cons |   .6106165   .0715313     8.54   0.000     .4703413    .7508917
-------------------------------------------------------------------------------------
table_s3.xls
dir : seeout
note: zero_sex omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      2,236
                                                F(16, 2219)       =       8.03
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0533
                                                Root MSE          =      .3751

-------------------------------------------------------------------------------------
                    |               Robust
out_priority_enviro | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |   -.024697    .015921    -1.55   0.121    -.0559186    .0065247
           zero_sex |          0  (omitted)
 cand_policy_abort1 |  -.1124986   .0249619    -4.51   0.000    -.1614497   -.0635474
 cand_policy_abort2 |  -.1175461   .0255827    -4.59   0.000    -.1677146   -.0673776
   cand_policy_tax1 |  -.0971473   .0248424    -3.91   0.000     -.145864   -.0484305
   cand_policy_tax2 |  -.1181796   .0248144    -4.76   0.000    -.1668415   -.0695176
cand_policy_health1 |  -.1005546   .0245181    -4.10   0.000    -.1486355   -.0524738
cand_policy_health2 |  -.0935098   .0256813    -3.64   0.000    -.1438717   -.0431479
   cand_policy_eco1 |   .0988589   .0222448     4.44   0.000     .0552361    .1424817
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          white_aa1 |  -.0270215   .0325686    -0.83   0.407    -.0908896    .0368467
          white_aa2 |  -.0168222   .0324634    -0.52   0.604    -.0804841    .0468396
          white_aa3 |  -.0457432   .0315299    -1.45   0.147    -.1075743     .016088
          black_aa0 |     .01847   .0306061     0.60   0.546    -.0415496    .0784895
          black_aa1 |  -.0292617   .0321346    -0.91   0.363    -.0922786    .0337553
          black_aa2 |  -.0222087   .0321837    -0.69   0.490     -.085322    .0409047
          black_aa3 |  -.0443967   .0321084    -1.38   0.167    -.1073624     .018569
           cand_age |  -.0010971   .0013265    -0.83   0.408    -.0036984    .0015041
              _cons |   .7863283   .0779699    10.09   0.000     .6334268    .9392299
-------------------------------------------------------------------------------------
table_s3.xls
dir : seeout
note: zero_sex omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      2,232
                                                F(16, 2215)       =      11.02
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0732
                                                Root MSE          =     .38074

-------------------------------------------------------------------------------------
                    |               Robust
 out_priority_abort | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |   .0396296   .0161778     2.45   0.014     .0079044    .0713549
           zero_sex |          0  (omitted)
 cand_policy_abort1 |   .2025557   .0254724     7.95   0.000     .1526035     .252508
 cand_policy_abort2 |    .160776   .0253898     6.33   0.000     .1109857    .2105663
   cand_policy_tax1 |  -.0211657   .0253891    -0.83   0.405    -.0709547    .0286232
   cand_policy_tax2 |   .0134439    .024831     0.54   0.588    -.0352505    .0621383
cand_policy_health1 |  -.0361674   .0250501    -1.44   0.149    -.0852915    .0129567
cand_policy_health2 |  -.0307992   .0259663    -1.19   0.236    -.0817201    .0201217
   cand_policy_eco1 |    -.01473    .022806    -0.65   0.518    -.0594534    .0299935
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          white_aa1 |   .0021227   .0324861     0.07   0.948    -.0615837    .0658291
          white_aa2 |  -.0023917   .0328784    -0.07   0.942    -.0668673     .062084
          white_aa3 |  -.0572667   .0312265    -1.83   0.067    -.1185031    .0039696
          black_aa0 |  -.0167364   .0312015    -0.54   0.592    -.0779237    .0444508
          black_aa1 |  -.0313619   .0324805    -0.97   0.334    -.0950573    .0323335
          black_aa2 |  -.0188216   .0327956    -0.57   0.566    -.0831349    .0454917
          black_aa3 |  -.0475302   .0313888    -1.51   0.130    -.1090848    .0140243
           cand_age |  -.0018714   .0013196    -1.42   0.156    -.0044592    .0007164
              _cons |   .5915374    .076636     7.72   0.000     .4412515    .7418233
-------------------------------------------------------------------------------------
table_s3.xls
dir : seeout
note: zero_sex omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      2,238
                                                F(16, 2221)       =       1.71
                                                Prob > F          =     0.0386
                                                R-squared         =     0.0120
                                                Root MSE          =     .37418

-------------------------------------------------------------------------------------
                    |               Robust
  out_priority_crim | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |  -.0295402    .015834    -1.87   0.062    -.0605912    .0015109
           zero_sex |          0  (omitted)
 cand_policy_abort1 |  -.0587155   .0248094    -2.37   0.018    -.1073676   -.0100634
 cand_policy_abort2 |  -.0394615   .0250791    -1.57   0.116    -.0886425    .0097196
   cand_policy_tax1 |  -.0376102   .0248572    -1.51   0.130     -.086356    .0111356
   cand_policy_tax2 |   .0048752   .0245768     0.20   0.843    -.0433208    .0530712
cand_policy_health1 |  -.0489906   .0244894    -2.00   0.046    -.0970151    -.000966
cand_policy_health2 |  -.0564547   .0260101    -2.17   0.030    -.1074613   -.0054482
   cand_policy_eco1 |  -.0143481   .0227487    -0.63   0.528     -.058959    .0302627
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          white_aa1 |   .0110803    .032417     0.34   0.733    -.0524905    .0746511
          white_aa2 |    -.00668   .0319901    -0.21   0.835    -.0694136    .0560536
          white_aa3 |  -.0058877   .0308677    -0.19   0.849    -.0664202    .0546448
          black_aa0 |   .0529561   .0310227     1.71   0.088    -.0078805    .1137926
          black_aa1 |   .0559737   .0318529     1.76   0.079    -.0064909    .1184383
          black_aa2 |   .0429754   .0313938     1.37   0.171    -.0185889    .1045397
          black_aa3 |   .0309428   .0311461     0.99   0.321    -.0301356    .0920213
           cand_age |  -.0010087    .001324    -0.76   0.446    -.0036052    .0015877
              _cons |   .6055852   .0765585     7.91   0.000     .4554516    .7557189
-------------------------------------------------------------------------------------
table_s3.xls
dir : seeout
note: zero_sex omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      2,237
                                                F(16, 2220)       =       2.61
                                                Prob > F          =     0.0005
                                                R-squared         =     0.0180
                                                Root MSE          =      .3518

-------------------------------------------------------------------------------------
                    |               Robust
    out_priority_sj | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |  -.0254704   .0149464    -1.70   0.089    -.0547808    .0038401
           zero_sex |          0  (omitted)
 cand_policy_abort1 |    .002989   .0233995     0.13   0.898    -.0428983    .0488762
 cand_policy_abort2 |    .011259   .0237727     0.47   0.636    -.0353599     .057878
   cand_policy_tax1 |   .0243487   .0236005     1.03   0.302    -.0219326    .0706301
   cand_policy_tax2 |   .0187225   .0231288     0.81   0.418    -.0266338    .0640788
cand_policy_health1 |   .0122916   .0228099     0.54   0.590    -.0324394    .0570226
cand_policy_health2 |   .0170047   .0242816     0.70   0.484    -.0306124    .0646218
   cand_policy_eco1 |   .0341733   .0212082     1.61   0.107    -.0074166    .0757633
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          white_aa1 |   .0598439   .0305666     1.96   0.050    -.0000982     .119786
          white_aa2 |   .0715095   .0310534     2.30   0.021     .0106128    .1324063
          white_aa3 |   .0403596   .0291768     1.38   0.167    -.0168571    .0975764
          black_aa0 |   .0298594   .0298884     1.00   0.318    -.0287528    .0884716
          black_aa1 |   .1414099   .0292767     4.83   0.000     .0839973    .1988224
          black_aa2 |   .0855879    .030291     2.83   0.005     .0261861    .1449896
          black_aa3 |   .1118929   .0291026     3.84   0.000     .0548217    .1689641
           cand_age |   .0014646   .0012258     1.19   0.232    -.0009392    .0038683
              _cons |    .488685   .0727609     6.72   0.000     .3459985    .6313716
-------------------------------------------------------------------------------------
table_s3.xls
dir : seeout
table_s2_fig2results.xls
dir : seeout

.                 
.         // Column 3 (fairness)
.         reg out_fair_bwdiff `reg_sex' `reg_issues' `int' cand_age , robust
note: zero_sex omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      2,241
                                                F(16, 2224)       =       4.58
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0313
                                                Root MSE          =      .3793

-------------------------------------------------------------------------------------
                    |               Robust
    out_fair_bwdiff | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |   .0321077   .0160745     2.00   0.046     .0005852    .0636303
           zero_sex |          0  (omitted)
 cand_policy_abort1 |   .0086124   .0256202     0.34   0.737    -.0416296    .0588544
 cand_policy_abort2 |   .0013976    .024918     0.06   0.955    -.0474673    .0502626
   cand_policy_tax1 |   .0146129   .0250636     0.58   0.560    -.0345376    .0637633
   cand_policy_tax2 |   .0290748   .0237573     1.22   0.221    -.0175141    .0756637
cand_policy_health1 |   .0294106   .0239024     1.23   0.219    -.0174629     .076284
cand_policy_health2 |   .0346009   .0274645     1.26   0.208    -.0192579    .0884598
   cand_policy_eco1 |   .0430522   .0230167     1.87   0.062    -.0020842    .0881887
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          white_aa1 |   .0909294   .0323785     2.81   0.005     .0274342    .1544246
          white_aa2 |   .0759166   .0326236     2.33   0.020     .0119407    .1398926
          white_aa3 |  -.0207179   .0302376    -0.69   0.493    -.0800147    .0385789
          black_aa0 |   .0964004   .0298165     3.23   0.001     .0379293    .1548715
          black_aa1 |   .1717674   .0315848     5.44   0.000     .1098286    .2337061
          black_aa2 |   .1516686   .0329466     4.60   0.000     .0870592     .216278
          black_aa3 |   .1130105   .0305455     3.70   0.000     .0531098    .1729112
           cand_age |   .0004088   .0013256     0.31   0.758    -.0021908    .0030084
              _cons |  -.0799885   .0770036    -1.04   0.299    -.2309949     .071018
-------------------------------------------------------------------------------------

.                 outreg2 using table_s2_fig2results.xls, append ctitle(Fairness)
table_s2_fig2results.xls
dir : seeout

.                 eststo r_out_fair_bwdiff

.                 loc b_fair = string(round(_b[_cons], 0.001), "%9.3f")

. 
.         // Fairness and Issue priority
.         foreach var of varlist out_fair_bwdiff out_priority_* {
  2.                 loc s = subinstr("`var'", "out_fair_", "", .)
  3.                 loc s = subinstr("`s'", "out_priority_", "", .)
  4.                 
.                 // Fairness
.                 if "`s'" == "bwdiff" loc tit "(b) Perceived Group Fairness: (Fairness to white) - (Fairn
> ess to Black)"
  5.                 // Priority
.                 if "`s'" == "tax" loc tit "Tax Policy"
  6.                 if "`s'" == "job" loc tit "Job Creation"
  7.                 if "`s'" == "health" loc tit "Healthcare"
  8.                 if "`s'" == "enviro" loc tit "Environmental Policy"
  9.                 if "`s'" == "abort" loc tit "Abortion"
 10.                 if "`s'" == "crim" loc tit "Criminal Justice Reform"
 11.                 if "`s'" == "sj" loc tit "Social Justice Issues"
 12.                         
.                 coefplot (r_`var', mc(gs4) ciopts(lw(med) color(gs4))) ///
>                         , drop(_cons `reg_issues' `reg_sex' cand_age) omitted baselevels ms(c) msize(s) 
> ylabel(,labsize(vsmall)) ///
>                         xline(0, lc(black)) nokey ///
>                         subtitle("{bf:`tit'}", bcolor(white) size(small) box pos(12) ///
>                                 bmargin(small) bexpand margin(small)) ///
>                         headings(white_aa0 = "{bf: No Affirmative Action}" ///
>                                         white_aa1 = "{bf: White X Affirmative Action}" ///
>                                         black_aa1 = "{bf: Black X Affirmative Action}", labsize(vsmall))
>  ///
>                         xlabel(-0.2(0.1)0.2,labsize(small)) norecycle saving(f_`var'.gph, replace)
 13.         }
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style s not found in class symbolsize, default attributes used)
(file f_out_fair_bwdiff.gph not found)
file f_out_fair_bwdiff.gph saved
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style s not found in class symbolsize, default attributes used)
(file f_out_priority_tax.gph not found)
file f_out_priority_tax.gph saved
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style s not found in class symbolsize, default attributes used)
(file f_out_priority_job.gph not found)
file f_out_priority_job.gph saved
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style s not found in class symbolsize, default attributes used)
(file f_out_priority_health.gph not found)
file f_out_priority_health.gph saved
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style s not found in class symbolsize, default attributes used)
(file f_out_priority_enviro.gph not found)
file f_out_priority_enviro.gph saved
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style s not found in class symbolsize, default attributes used)
(file f_out_priority_abort.gph not found)
file f_out_priority_abort.gph saved
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style s not found in class symbolsize, default attributes used)
(file f_out_priority_crim.gph not found)
file f_out_priority_crim.gph saved
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style s not found in class symbolsize, default attributes used)
(file f_out_priority_sj.gph not found)
file f_out_priority_sj.gph saved

.         
.         coefplot (ideo, label() mc(gs4) ciopts(color(gs4) lw(med))) ///
>                                 , bylabel("{bf:(a) Ideological Liberalness}") || ///
>                          (r_out_priority_sj, label() mc(gs4) ciopts(color(gs4) lw(med))) ///
>                                 , bylabel("{bf:(b) Prioritize Social Justice}") || ///
>                         (r_out_fair_bwdiff, label() mc(gs4) ciopts(color(gs4) lw(med))) ///
>                                 , bylabel("{bf:(c) Fairer to Black than White Constituents}") ///
>                         || , drop(_cons `reg_sex' `reg_issues' cand_age) omitted baselevels ms(c) msize(
> med) ///
>                         ylabel(,labsize(vsmall)) ///
>                 xline(0, lc(black)) nokey ///
>                 subtitle(, bcolor(white) color(black) size(vsmall)) ///
>                 byopts(row(1) t1title("{bf:`title'}", size(small))) ///
>                 xtitle("Effects of Candidate Attributes (Scale 0 to 1)", size(vsmall)) ///
>                 xlabel(-0.2(0.1)0.2,labsize(small)) norecycle ///
>                 headings(white_aa0 = "{bf: White X Affirmative Action}" ///
>                         black_aa0 = "{bf: Black X Affirmative Action}", labsize(vsmall))
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)

. 
.                 addplot 1: ,note("Mean, Baseline Categories = `b_ideo'", size(vsmall)) norescaling

.                 addplot 2: ,note("Mean, Baseline Categories = `b_sj'", size(vsmall)) norescaling        
>         

.                 addplot 3: ,note("Mean, Baseline Categories = `b_fair'", size(vsmall)) norescaling      
>         

. 
.                 graph display, xsize(4.5) ysize(3.4) margins(vsmall)    

.                 graph export figure_2.png, as(png) replace
(file figure_2.png not found)
file figure_2.png saved as PNG format

.         
.         
. /* 
>         Figure S1b. Pre-registered specification of Figure 1.
> */
. 
.         use data_study_1.dta, clear

. 
. // Set omitted categories
.         gen zero_race = 0

.         label var zero_race "White"

.         gen zero_sex = 0

.         label var zero_sex "Male"

.         gen zero_eco = 0

.         label var zero_eco "Maintain investment in energy"

.         gen zero_aa = 0

.         label var zero_aa "Not shown policy"

. 
. // Create pairings (1 = liberal, 2 = moderate)
.         cap drop policy*

.         egen policy1 = rowtotal(cand_policy_abort1 cand_policy_tax1 cand_policy_health1 cand_policy_eco1
> )

.         egen policy2 = rowtotal(cand_policy_abort2 cand_policy_tax2 cand_policy_health2 cand_policy_eco2
> )

. 
.         gen policy_LL = policy1 == 2

.         gen policy_LM = policy1 == 1 & policy2 == 1

.         gen policy_MM = policy2 == 2

. 
.         
.         // Set regression variables
.         loc reg_race "cand_black zero_race"

.         loc reg_sex "cand_female zero_sex"

.         loc reg_issues "policy_LM policy_MM"

.         loc reg_affirm "cand_policy_aa1 cand_policy_aa2 cand_policy_aa3 zero_aa"

.         
. // Interactive Terms for Black Candidate X Affirmative Action
.         gen noracepolicy = cand_policy_aa1 == 0 & cand_policy_aa2 == 0 & cand_policy_aa3 == 0   

.         gen black_aa1 = cand_policy_aa1*cand_black

.         gen black_aa2 = cand_policy_aa2*cand_black

.         gen black_aa3 = cand_policy_aa3*cand_black

.         gen white_aa1 = cand_policy_aa1*cand_white

.         gen white_aa2 = cand_policy_aa2*cand_white

.         gen white_aa3 = cand_policy_aa3*cand_white

.         label var black_aa1 "Black X Expand (race)"

.         label var black_aa2 "Black X Keep as is"

.         label var black_aa3 "Black X Replace (class)"

.         label var white_aa1 "White X Expand (race)"

.         label var white_aa2 "White X Keep as is"

.         label var white_aa3 "White X Replace (class)"

.         label var noracepolicy "Not shown position"

.         
.         loc int "white_aa1 white_aa2 white_aa3 black_aa1 black_aa2 black_aa3"

.         
.         gen out_fair_bwdiff = out_fair_black - out_fair_white
(226 missing values generated)

. 
.         // Table
.         reg out_ideo_7 `reg_race' `reg_sex' cand_age `reg_issues' `reg_affirm', robust
note: zero_race omitted because of collinearity.
note: zero_sex omitted because of collinearity.
note: zero_aa omitted because of collinearity.

Linear regression                               Number of obs     =      2,339
                                                F(8, 2330)        =       2.83
                                                Prob > F          =     0.0040
                                                R-squared         =     0.0094
                                                Root MSE          =     .26182

---------------------------------------------------------------------------------
                |               Robust
     out_ideo_7 | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------+----------------------------------------------------------------
     cand_black |   .0297254   .0108453     2.74   0.006     .0084581    .0509928
      zero_race |          0  (omitted)
    cand_female |   .0030635   .0108314     0.28   0.777    -.0181768    .0243037
       zero_sex |          0  (omitted)
       cand_age |  -.0008584   .0008962    -0.96   0.338    -.0026158    .0008991
      policy_LM |  -.0323257   .0134034    -2.41   0.016    -.0586095    -.006042
      policy_MM |  -.0454886    .014641    -3.11   0.002    -.0741994   -.0167778
cand_policy_aa1 |    .019487   .0150258     1.30   0.195    -.0099782    .0489523
cand_policy_aa2 |   .0060145   .0158137     0.38   0.704    -.0249958    .0370249
cand_policy_aa3 |  -.0071269   .0149325    -0.48   0.633    -.0364094    .0221555
        zero_aa |          0  (omitted)
          _cons |   .7307487   .0459001    15.92   0.000     .6407394     .820758
---------------------------------------------------------------------------------

.         outreg2 using table_s1b.xls, replace ctitle(Ideological Liberalness)
table_s1b.xls
dir : seeout

.         
.         reg out_priority_sj `reg_race' `reg_sex' cand_age `reg_issues' `reg_affirm', robust
note: zero_race omitted because of collinearity.
note: zero_sex omitted because of collinearity.
note: zero_aa omitted because of collinearity.

Linear regression                               Number of obs     =      2,237
                                                F(8, 2228)        =       4.39
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0154
                                                Root MSE          =     .35164

---------------------------------------------------------------------------------
                |               Robust
out_priority_sj | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------+----------------------------------------------------------------
     cand_black |   .0498896   .0148785     3.35   0.001     .0207124    .0790668
      zero_race |          0  (omitted)
    cand_female |  -.0248763   .0148876    -1.67   0.095    -.0540712    .0043187
       zero_sex |          0  (omitted)
       cand_age |   .0014937   .0012284     1.22   0.224    -.0009152    .0039026
      policy_LM |  -.0197781   .0180403    -1.10   0.273    -.0551557    .0155995
      policy_MM |  -.0129634    .020398    -0.64   0.525    -.0529645    .0270377
cand_policy_aa1 |   .0861039   .0210314     4.09   0.000     .0448608     .127347
cand_policy_aa2 |   .0644422    .021625     2.98   0.003      .022035    .1068495
cand_policy_aa3 |   .0604076    .020523     2.94   0.003     .0201615    .1006538
        zero_aa |          0  (omitted)
          _cons |   .5194327   .0646219     8.04   0.000     .3927073     .646158
---------------------------------------------------------------------------------

.         outreg2 using table_s1b.xls, append ctitle(Prioritize Social Justice)
table_s1b.xls
dir : seeout

.         
.         reg out_fair_bwdiff `reg_race' `reg_sex' cand_age `reg_issues' `reg_affirm', robust
note: zero_race omitted because of collinearity.
note: zero_sex omitted because of collinearity.
note: zero_aa omitted because of collinearity.

Linear regression                               Number of obs     =      2,241
                                                F(8, 2232)        =       8.00
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0280
                                                Root MSE          =     .37927

---------------------------------------------------------------------------------
                |               Robust
out_fair_bwdiff | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------+----------------------------------------------------------------
     cand_black |   .0974235   .0160285     6.08   0.000     .0659912    .1288557
      zero_race |          0  (omitted)
    cand_female |   .0327719    .016002     2.05   0.041     .0013915    .0641523
       zero_sex |          0  (omitted)
       cand_age |   .0003886   .0013283     0.29   0.770    -.0022162    .0029934
      policy_LM |  -.0107001   .0193982    -0.55   0.581    -.0487404    .0273403
      policy_MM |  -.0143546   .0218979    -0.66   0.512     -.057297    .0285878
cand_policy_aa1 |   .0822496   .0223359     3.68   0.000     .0384484    .1260508
cand_policy_aa2 |   .0648186   .0229174     2.83   0.005     .0198769    .1097603
cand_policy_aa3 |  -.0031427   .0212754    -0.15   0.883    -.0448644    .0385789
        zero_aa |          0  (omitted)
          _cons |  -.0306269   .0703724    -0.44   0.663    -.1686292    .1073753
---------------------------------------------------------------------------------

.         outreg2 using table_s1b.xls, append ctitle(Fairness to Black over White)
table_s1b.xls
dir : seeout

.         
. 
end of do-file

. do 3_study2_analysis.do

. /*
>         Figure 3. Main Effects of Candidate Race on Inferred Ideology and Group Favoritism
>         Corresponds to Table S4 in Appendix
>         
>         Figure 4. Interacted results
>         Corresponds to Table S5 in Appendix.
>         
> */
. 
. use data_study_2.dta, clear

. 
. 
. // Set omitted categories
.         gen zero_race = 0

.         label var zero_race "White"

.         gen zero_sex = 0

.         label var zero_sex "Male"

.         gen zero_eco = 0

.         label var zero_eco "Maintain investment in energy"

.         gen zero_biden = 0

.         label var zero_biden "Vote Share: 51%"

.         gen zero_exp = 0

.         label var zero_exp "Political newcomer"

.         gen zero_dist = 0

.         label var zero_dist "[63, 8, 13, 11, 5]"

.         gen zero_racepol = 0

.         label var zero_racepol "Not shown policy"

.         
. // Set regression variables
.         loc reg_race "cand_black zero_race cand_asian cand_hispa"

.         loc reg_sex "cand_female zero_sex"

.         loc reg_exp "cand_exp_teach cand_exp_council cand_exp_lawyer cand_exp_business zero_exp"

.         loc reg_biden "cand_biden_p59 cand_biden_p57 cand_biden_p55 cand_biden_p53 zero_biden"

.         loc reg_distpop "cand_dist1 cand_dist2 cand_dist3 cand_dist4 cand_dist5 cand_dist6 zero_dist"

.         loc reg_issues "cand_policy_abort1 cand_policy_abort2 cand_policy_tax1 cand_policy_tax2"

.         loc reg_issues "`reg_issues' cand_policy_health1 cand_policy_health2 cand_policy_eco1 zero_eco"

.         loc reg_affirm "cand_policy_aa1 cand_policy_aa2 cand_policy_aa3 zero_racepol"

.         loc reg_affirm2 "noracepolicy cand_policy_aa1 cand_policy_aa2 cand_policy_aa3 "

.         
. // Interactive Terms for Black Candidate X Affirmative Action
.         gen noracepolicy = cand_policy_aa1 == 0 & cand_policy_aa2 == 0 & cand_policy_aa3 == 0   

.         
.         loc int ""

.         foreach r in white black asian hispa {
  2.                 gen `r'_aa1 = cand_policy_aa1*cand_`r'
  3.                 gen `r'_aa2 = cand_policy_aa2*cand_`r'
  4.                 gen `r'_aa3 = cand_policy_aa3*cand_`r'
  5.                 gen `r'_aa0 = noracepolicy*cand_`r'
  6.                 
.                 loc lab = proper("`r'")
  7.                 if "`lab'" == "Hispa" loc lab = "Hispanic"
  8.         
.                 label var `r'_aa0 "`lab' X No Position"
  9.                 label var `r'_aa1 "`lab' X Expand"
 10.                 label var `r'_aa2 "`lab' X Keep"
 11.                 label var `r'_aa3 "`lab' X End"
 12.                 
.                 loc int "`int' `r'_aa0 `r'_aa1 `r'_aa2 `r'_aa3"
 13.         
.         }

.         // set reference policy
.         replace white_aa0 = 0
(560 real changes made)

.         label var noracepolicy "Not shown position"

.         
.         gen out_fair_bwdiff = out_fair_black - out_fair_white
(2 missing values generated)

.                 
. //============================================================================== Regress the things
. 
. 
.         // All attributes, pooled 
.         eststo clear

.         
.         reg out_ideo `reg_distpop' `reg_race' `reg_affirm' `reg_issues' `reg_sex' cand_age `reg_exp' `re
> g_biden', vce(cluster r_id)
note: zero_dist omitted because of collinearity.
note: zero_race omitted because of collinearity.
note: zero_racepol omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: zero_sex omitted because of collinearity.
note: zero_exp omitted because of collinearity.
note: zero_biden omitted because of collinearity.

Linear regression                               Number of obs     =      7,230
                                                F(29, 1446)       =       8.83
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0364
                                                Root MSE          =     .23862

                                      (Std. err. adjusted for 1,447 clusters in r_id)
-------------------------------------------------------------------------------------
                    |               Robust
           out_ideo | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
         cand_dist1 |   -.011427   .0085282    -1.34   0.180    -.0281559     .005302
         cand_dist2 |  -.0088909   .0083444    -1.07   0.287    -.0252593    .0074776
         cand_dist3 |  -.0161744   .0086248    -1.88   0.061    -.0330929    .0007441
         cand_dist4 |  -.0079575   .0086475    -0.92   0.358    -.0249206    .0090056
         cand_dist5 |  -.0149592   .0089213    -1.68   0.094    -.0324592    .0025408
         cand_dist6 |  -.0179874   .0085165    -2.11   0.035    -.0346934   -.0012814
          zero_dist |          0  (omitted)
         cand_black |    .009255   .0060413     1.53   0.126    -.0025957    .0211057
          zero_race |          0  (omitted)
         cand_asian |   .0019477   .0060728     0.32   0.748    -.0099646    .0138601
         cand_hispa |   .0101125    .005887     1.72   0.086    -.0014355    .0216604
    cand_policy_aa1 |   .0258868   .0082687     3.13   0.002     .0096669    .0421067
    cand_policy_aa2 |   .0224105   .0083957     2.67   0.008     .0059415    .0388795
    cand_policy_aa3 |  -.0434348   .0084995    -5.11   0.000    -.0601074   -.0267622
       zero_racepol |          0  (omitted)
 cand_policy_abort1 |   .0867143   .0093129     9.31   0.000     .0684462    .1049825
 cand_policy_abort2 |   .0224237   .0085699     2.62   0.009     .0056129    .0392345
   cand_policy_tax1 |   .0105458   .0091488     1.15   0.249    -.0074005    .0284921
   cand_policy_tax2 |  -.0152856   .0088361    -1.73   0.084    -.0326186    .0020473
cand_policy_health1 |   .0341998   .0088759     3.85   0.000     .0167888    .0516108
cand_policy_health2 |   .0067776   .0087752     0.77   0.440    -.0104359     .023991
   cand_policy_eco1 |   .0136099   .0075939     1.79   0.073    -.0012863    .0285061
           zero_eco |          0  (omitted)
        cand_female |   .0060332   .0046498     1.30   0.195    -.0030878    .0151543
           zero_sex |          0  (omitted)
           cand_age |  -.0006948   .0004646    -1.50   0.135    -.0016061    .0002165
     cand_exp_teach |   .0123271   .0065478     1.88   0.060    -.0005171    .0251713
   cand_exp_council |   .0052551   .0063992     0.82   0.412    -.0072976    .0178079
    cand_exp_lawyer |     .00317   .0066268     0.48   0.632    -.0098292    .0161692
  cand_exp_business |   .0055575   .0065044     0.85   0.393    -.0072015    .0183166
           zero_exp |          0  (omitted)
     cand_biden_p59 |   .0001427   .0066168     0.02   0.983    -.0128367    .0131222
     cand_biden_p57 |   .0106923   .0065854     1.62   0.105    -.0022256    .0236102
     cand_biden_p55 |   .0031505   .0063996     0.49   0.623     -.009403    .0157041
     cand_biden_p53 |    .003355   .0062989     0.53   0.594     -.009001     .015711
         zero_biden |          0  (omitted)
              _cons |   .6738899    .027898    24.16   0.000      .619165    .7286149
-------------------------------------------------------------------------------------

.                 eststo pool_ideo

.                 loc b_pool_ideo = string(round(_b[_cons], 0.001), "%9.3f")

.                 outreg2 using table_s4_fig3results.xls, replace ctitle(Ideological Liberalness)
table_s4_fig3results.xls
dir : seeout

.                 
.         reg out_fair_bwdiff `reg_distpop' `reg_race' `reg_affirm' `reg_issues' `reg_sex' cand_age `reg_e
> xp' `reg_biden', vce(cluster r_id)
note: zero_dist omitted because of collinearity.
note: zero_race omitted because of collinearity.
note: zero_racepol omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: zero_sex omitted because of collinearity.
note: zero_exp omitted because of collinearity.
note: zero_biden omitted because of collinearity.

Linear regression                               Number of obs     =      7,233
                                                F(29, 1446)       =      14.04
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0653
                                                Root MSE          =     .37225

                                      (Std. err. adjusted for 1,447 clusters in r_id)
-------------------------------------------------------------------------------------
                    |               Robust
    out_fair_bwdiff | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
         cand_dist1 |   .0476531   .0145354     3.28   0.001     .0191404    .0761658
         cand_dist2 |   .0753717   .0149865     5.03   0.000     .0459741    .1047693
         cand_dist3 |   .0842905    .015919     5.29   0.000     .0530637    .1155174
         cand_dist4 |   .0294024   .0144037     2.04   0.041     .0011479    .0576568
         cand_dist5 |   .0074005   .0149824     0.49   0.621    -.0219891    .0367901
         cand_dist6 |   .0191165   .0143248     1.33   0.182    -.0089831    .0472161
          zero_dist |          0  (omitted)
         cand_black |   .1984642   .0121063    16.39   0.000     .1747165    .2222118
          zero_race |          0  (omitted)
         cand_asian |   .0686829   .0099904     6.87   0.000     .0490858    .0882801
         cand_hispa |   .0768654   .0102886     7.47   0.000     .0566832    .0970477
    cand_policy_aa1 |   .0550258   .0128767     4.27   0.000     .0297668    .0802847
    cand_policy_aa2 |   .0469467   .0123962     3.79   0.000     .0226301    .0712632
    cand_policy_aa3 |  -.0674685   .0120448    -5.60   0.000    -.0910956   -.0438414
       zero_racepol |          0  (omitted)
 cand_policy_abort1 |   .0159245    .013649     1.17   0.244    -.0108494    .0426984
 cand_policy_abort2 |   .0055988    .013015     0.43   0.667    -.0199315    .0311292
   cand_policy_tax1 |   .0261939   .0133741     1.96   0.050    -.0000408    .0524286
   cand_policy_tax2 |   .0195506   .0132069     1.48   0.139    -.0063561    .0454573
cand_policy_health1 |   .0168457   .0133616     1.26   0.208    -.0093645     .043056
cand_policy_health2 |   .0248465   .0133922     1.86   0.064    -.0014238    .0511167
   cand_policy_eco1 |   .0227985   .0121631     1.87   0.061    -.0010608    .0466577
           zero_eco |          0  (omitted)
        cand_female |    .014205   .0076036     1.87   0.062    -.0007103    .0291202
           zero_sex |          0  (omitted)
           cand_age |   -.000109   .0007101    -0.15   0.878    -.0015019    .0012839
     cand_exp_teach |  -.0112972   .0111942    -1.01   0.313    -.0332557    .0106614
   cand_exp_council |   .0048714    .011252     0.43   0.665    -.0172005    .0269433
    cand_exp_lawyer |  -.0102383   .0117674    -0.87   0.384    -.0333214    .0128448
  cand_exp_business |  -.0095326   .0112929    -0.84   0.399    -.0316847    .0126195
           zero_exp |          0  (omitted)
     cand_biden_p59 |   .0077247   .0116267     0.66   0.507    -.0150823    .0305317
     cand_biden_p57 |   .0024953   .0113039     0.22   0.825    -.0196786    .0246692
     cand_biden_p55 |    .020742   .0116792     1.78   0.076     -.002168     .043652
     cand_biden_p53 |   .0124567   .0113656     1.10   0.273    -.0098381    .0347514
         zero_biden |          0  (omitted)
              _cons |  -.0816818   .0426365    -1.92   0.056    -.1653179    .0019542
-------------------------------------------------------------------------------------

.                 eststo pool_fair

.                 loc b_pool_fair = string(round(_b[_cons], 0.001), "%9.3f")

.                 outreg2 using table_s4_fig3results.xls, append ctitle(Group Favoritism)
table_s4_fig3results.xls
dir : seeout

.                 
.         coefplot (pool_ideo, label() mc(gs4) ciopts(color(gs4) lw(med))) ///
>                                 , bylabel("{bf:(a) Ideological Liberalness}") || ///
>                         (pool_fair, label() mc(gs4) ciopts(color(gs4) lw(med))) ///
>                                 , bylabel("{bf:(b) Prioritize Black over White Constituents}") ///
>                         || , drop(_cons cand_age) omitted baselevels ms(c) msize(medsmall) ///
>                         ylabel(,labsize(vsmall)) ///
>                 xline(0, lc(black)) nokey ///
>                 subtitle(, bcolor(white) color(black) size(vsmall)) ///
>                 byopts(row(1) note("`notes'", size(vsmall)) t1title("{bf:`title'}", size(small))) ///
>                 xtitle("Effects of Candidate Attributes (Scale 0 to 1)", size(vsmall)) ///
>                 xlabel(-0.2(0.1)0.2,labsize(small)) norecycle ///
>                 headings(cand_black = "{bf: Race}" ///
>                                 cand_female = "{bf: Gender}" ///
>                                 cand_exp_teach = "{bf: Occupation}" ///
>                                 cand_biden_p59 = "{bf: District Vote for Biden}" ///
>                                 cand_dist1 = "{bf: District Racial % [W,B,A,H,O]}" ///
>                                 cand_policy_abort1 = "{bf: Abortion}" ///
>                                 cand_policy_tax1 = "{bf: Tax Policy}" ///
>                                 cand_policy_health1 = "{bf: Healthcare}" ///
>                                 cand_policy_eco1 = "{bf: Energy}" ///
>                                 cand_policy_aa1 = "{bf: Affirmative Action}" ///
>                                 , labsize(vsmall)) 
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)

. 
.                 addplot 1: ,note("Mean, Baseline Categories = `b_pool_ideo'", size(vsmall)) norescaling

.                 addplot 2: ,note("Mean, Baseline Categories = `b_pool_fair'", size(vsmall)) norescaling

. 
.                 graph display, xsize(5) ysize(3.7) margins(vsmall)      

.                 graph export figure_3.png, as(png) replace
(file figure_3.png not found)
file figure_3.png saved as PNG format

.         
.         // Effect of candidate attributes on main outcomes, interacted
.         reg out_ideo `reg_sex' `reg_exp' `reg_biden' `reg_distpop' `reg_issues' `int' cand_age, vce(clus
> ter r_id)       
note: zero_sex omitted because of collinearity.
note: zero_exp omitted because of collinearity.
note: zero_biden omitted because of collinearity.
note: zero_dist omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      7,230
                                                F(38, 1446)       =       7.00
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0371
                                                Root MSE          =     .23868

                                      (Std. err. adjusted for 1,447 clusters in r_id)
-------------------------------------------------------------------------------------
                    |               Robust
           out_ideo | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |   .0059291   .0046498     1.28   0.202     -.003192    .0150501
           zero_sex |          0  (omitted)
     cand_exp_teach |   .0122159   .0065721     1.86   0.063    -.0006761    .0251078
   cand_exp_council |   .0051068   .0064179     0.80   0.426    -.0074826    .0176962
    cand_exp_lawyer |   .0030542   .0066661     0.46   0.647    -.0100221    .0161305
  cand_exp_business |   .0055399   .0065377     0.85   0.397    -.0072845    .0183642
           zero_exp |          0  (omitted)
     cand_biden_p59 |   .0000409   .0066104     0.01   0.995    -.0129261    .0130079
     cand_biden_p57 |   .0103569   .0066061     1.57   0.117    -.0026016    .0233154
     cand_biden_p55 |   .0030348   .0064071     0.47   0.636    -.0095334     .015603
     cand_biden_p53 |   .0030762   .0063017     0.49   0.626    -.0092852    .0154376
         zero_biden |          0  (omitted)
         cand_dist1 |  -.0113719   .0085274    -1.33   0.183    -.0280992    .0053555
         cand_dist2 |  -.0093389   .0083509    -1.12   0.264    -.0257201    .0070422
         cand_dist3 |  -.0159317   .0086303    -1.85   0.065     -.032861    .0009976
         cand_dist4 |  -.0078922   .0086635    -0.91   0.362    -.0248866    .0091022
         cand_dist5 |  -.0150726   .0089194    -1.69   0.091    -.0325689    .0024237
         cand_dist6 |  -.0179895   .0085356    -2.11   0.035    -.0347331   -.0012459
          zero_dist |          0  (omitted)
 cand_policy_abort1 |   .0865966   .0093206     9.29   0.000     .0683133    .1048799
 cand_policy_abort2 |   .0222603   .0085781     2.60   0.010     .0054334    .0390871
   cand_policy_tax1 |   .0099431   .0091723     1.08   0.279    -.0080493    .0279355
   cand_policy_tax2 |  -.0153925    .008837    -1.74   0.082    -.0327271    .0019421
cand_policy_health1 |   .0336736   .0088891     3.79   0.000     .0162367    .0511104
cand_policy_health2 |   .0063585   .0087873     0.72   0.469    -.0108788    .0235958
   cand_policy_eco1 |   .0132894   .0076099     1.75   0.081    -.0016382    .0282169
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          white_aa1 |   .0139106   .0144716     0.96   0.337     -.014477    .0422983
          white_aa2 |   .0115353   .0148021     0.78   0.436    -.0175006    .0405711
          white_aa3 |  -.0613646   .0146132    -4.20   0.000      -.09003   -.0326992
          black_aa0 |   -.005849   .0135541    -0.43   0.666    -.0324368    .0207389
          black_aa1 |   .0312423   .0134733     2.32   0.021     .0048129    .0576716
          black_aa2 |   .0155517    .014348     1.08   0.279    -.0125934    .0436968
          black_aa3 |   -.039669    .013763    -2.88   0.004    -.0666666   -.0126714
          asian_aa0 |   -.019575   .0149818    -1.31   0.192    -.0489633    .0098133
          asian_aa1 |   .0104106   .0151699     0.69   0.493    -.0193468    .0401679
          asian_aa2 |    .022626   .0151685     1.49   0.136    -.0071287    .0523807
          asian_aa3 |  -.0413389   .0147379    -2.80   0.005     -.070249   -.0124289
          hispa_aa0 |   .0032418   .0142965     0.23   0.821    -.0248022    .0312859
          hispa_aa1 |   .0261759   .0154693     1.69   0.091    -.0041688    .0565206
          hispa_aa2 |   .0247045    .014716     1.68   0.093    -.0041625    .0535714
          hispa_aa3 |  -.0491622   .0158941    -3.09   0.002    -.0803401   -.0179842
           cand_age |  -.0007007   .0004648    -1.51   0.132    -.0016124     .000211
              _cons |   .6851087    .028839    23.76   0.000     .6285379    .7416796
-------------------------------------------------------------------------------------

.                 eststo ideo

.                 loc b_ideo = string(round(_b[_cons], 0.001), "%9.3f")

.                 outreg2 using table_s5_fig4results.xls, replace ctitle(Ideological Liberalness)
table_s5_fig4results.xls
dir : seeout

.         
.         reg out_fair_bwdiff `reg_sex' `reg_exp' `reg_biden' `reg_distpop' `reg_issues' `int' cand_age , 
> vce(cluster r_id)
note: zero_sex omitted because of collinearity.
note: zero_exp omitted because of collinearity.
note: zero_biden omitted because of collinearity.
note: zero_dist omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      7,233
                                                F(38, 1446)       =      10.79
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0662
                                                Root MSE          =     .37231

                                      (Std. err. adjusted for 1,447 clusters in r_id)
-------------------------------------------------------------------------------------
                    |               Robust
    out_fair_bwdiff | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |   .0139265   .0076268     1.83   0.068    -.0010342    .0288872
           zero_sex |          0  (omitted)
     cand_exp_teach |  -.0112882   .0112302    -1.01   0.315    -.0333175     .010741
   cand_exp_council |   .0049001   .0112728     0.43   0.664    -.0172127     .027013
    cand_exp_lawyer |   -.010402   .0117992    -0.88   0.378    -.0335474    .0127434
  cand_exp_business |  -.0089442   .0113374    -0.79   0.430    -.0311838    .0132954
           zero_exp |          0  (omitted)
     cand_biden_p59 |   .0079005   .0116374     0.68   0.497    -.0149274    .0307284
     cand_biden_p57 |    .002314   .0112995     0.20   0.838    -.0198512    .0244792
     cand_biden_p55 |    .020527   .0117194     1.75   0.080    -.0024619    .0435159
     cand_biden_p53 |   .0122306   .0114134     1.07   0.284    -.0101581    .0346192
         zero_biden |          0  (omitted)
         cand_dist1 |   .0470683   .0146007     3.22   0.001     .0184276    .0757091
         cand_dist2 |   .0742289   .0150229     4.94   0.000     .0447599     .103698
         cand_dist3 |    .084251   .0159216     5.29   0.000     .0530191    .1154828
         cand_dist4 |   .0287881   .0144329     1.99   0.046     .0004764    .0570997
         cand_dist5 |   .0064837   .0150236     0.43   0.666    -.0229867    .0359542
         cand_dist6 |   .0183777   .0143633     1.28   0.201    -.0097974    .0465528
          zero_dist |          0  (omitted)
 cand_policy_abort1 |    .015618   .0136396     1.15   0.252    -.0111375    .0423735
 cand_policy_abort2 |   .0051392   .0130142     0.39   0.693    -.0203895     .030668
   cand_policy_tax1 |   .0252993   .0134408     1.88   0.060    -.0010662    .0516647
   cand_policy_tax2 |   .0194576   .0132096     1.47   0.141    -.0064544    .0453697
cand_policy_health1 |    .015918   .0133605     1.19   0.234    -.0102901    .0421262
cand_policy_health2 |   .0239248   .0133908     1.79   0.074    -.0023428    .0501923
   cand_policy_eco1 |   .0220292   .0121881     1.81   0.071     -.001879    .0459373
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          white_aa1 |   .0467187   .0229738     2.03   0.042     .0016532    .0917842
          white_aa2 |   .0410289   .0231961     1.77   0.077    -.0044727    .0865304
          white_aa3 |  -.1027482   .0221974    -4.63   0.000    -.1462908   -.0592056
          black_aa0 |   .1868773    .022748     8.22   0.000     .1422546       .2315
          black_aa1 |   .2470242   .0230655    10.71   0.000     .2017789    .2922696
          black_aa2 |   .2276338   .0230118     9.89   0.000     .1824938    .2727738
          black_aa3 |   .1179799   .0222085     5.31   0.000     .0744156    .1615442
          asian_aa0 |   .0384585   .0216096     1.78   0.075     -.003931     .080848
          asian_aa1 |    .095862   .0233697     4.10   0.000     .0500199    .1417041
          asian_aa2 |   .1096244   .0230638     4.75   0.000     .0643822    .1548665
          asian_aa3 |   .0160585   .0221627     0.72   0.469    -.0274159     .059533
          hispa_aa0 |   .0634578   .0200615     3.16   0.002     .0241051    .1028104
          hispa_aa1 |   .1206673   .0236912     5.09   0.000     .0741945    .1671401
          hispa_aa2 |   .1046724   .0233395     4.48   0.000     .0588895    .1504552
          hispa_aa3 |    .004609   .0228092     0.20   0.840    -.0401336    .0493517
           cand_age |  -.0000902   .0007096    -0.13   0.899    -.0014822    .0013017
              _cons |   -.068754   .0444104    -1.55   0.122    -.1558697    .0183617
-------------------------------------------------------------------------------------

.                 eststo fair_bwdiff

.                 loc b_fair = string(round(_b[_cons], 0.001), "%9.3f")

.                 outreg2 using table_s5_fig4results.xls, append ctitle(Group Favoritism)
table_s5_fig4results.xls
dir : seeout

.         
.         coefplot (ideo, label() mc(gs4) ciopts(color(gs4) lw(med))) ///
>                                 , bylabel("{bf:(a) Ideological Liberalness}") || ///
>                         (fair_bwdiff, label() mc(gs4) ciopts(color(gs4) lw(med))) ///
>                                 , bylabel("{bf:(b) Prioritize Black over White Constituents}") ///
>                         || , drop(_cons `reg_sex' `reg_issues' cand_age `reg_exp' `reg_biden' `reg_distp
> op') ///
>                         omitted baselevels ms(c) msize(med) ///
>                         ylabel(,labsize(vsmall)) ///
>                 xline(0, lc(black)) nokey ///
>                 subtitle(, bcolor(white) color(black) size(vsmall)) ///
>                 byopts(row(1) t1title("{bf:`title'}", size(small))) ///
>                 xtitle("Effects of Candidate Attributes (Scale 0 to 1)", size(vsmall)) ///
>                 xlabel(-0.2(0.1)0.2,labsize(small)) norecycle ///
>                 headings(white_aa0 = "{bf: White X Affirmative Action}" ///
>                                 black_aa0 = "{bf: Black X Affirmative Action}" ///
>                                 asian_aa0 = "{bf: Asian X Affirmative Action}" ///
>                                 hispa_aa0 = "{bf: Hispanic X Affirmative Action}" ///
>                                 , labsize(vsmall)) 
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)

. 
.                 addplot 1: ,note("Mean, Baseline Categories = `b_ideo'", size(vsmall)) norescaling

.                 addplot 2: ,note("Mean, Baseline Categories = `b_fair'", size(vsmall)) norescaling

.         
.                 graph display, xsize(4.5) ysize(3.4) margins(vsmall)    

.                 graph export figure_4.png, as(png) replace
(file figure_4.png not found)
file figure_4.png saved as PNG format

. 
.                 
.         
. 
.                 
. 
end of do-file

. do 4_study2_tables.do

. /*
>         Table 3 and Table 4
>         Differences in means tests for Study 1 and Study 2 respectively.
>         The code for the regressions here is the same as the code used to produce 
>         the main figures and tables.
> */
. 
. // Study 1 
. 
. use data_study_1.dta, clear

. 
. // Set omitted categories
.         gen zero_race = 0

.         label var zero_race "White"

.         gen zero_sex = 0

.         label var zero_sex "Male"

.         gen zero_eco = 0

.         label var zero_eco "Maintain investment in energy"

.         
. // Set regression variables
.         loc reg_race "cand_black zero_race"

.         loc reg_sex "cand_female zero_sex"

.         loc reg_issues "cand_policy_abort1 cand_policy_abort2 cand_policy_tax1 cand_policy_tax2"

.         loc reg_issues "`reg_issues' cand_policy_health1 cand_policy_health2 cand_policy_eco1 zero_eco"

.         loc reg_affirm "cand_policy_aa1 cand_policy_aa2 cand_policy_aa3"

.         
. // Interactive Terms for Black Candidate X Affirmative Action
.         gen noracepolicy = cand_policy_aa1 == 0 & cand_policy_aa2 == 0 & cand_policy_aa3 == 0   

.         gen black_aa1 = cand_policy_aa1*cand_black

.         gen black_aa2 = cand_policy_aa2*cand_black

.         gen black_aa3 = cand_policy_aa3*cand_black

.         gen white_aa1 = cand_policy_aa1*cand_white

.         gen white_aa2 = cand_policy_aa2*cand_white

.         gen white_aa3 = cand_policy_aa3*cand_white

.         gen black_aa0 = noracepolicy*cand_black

.         gen white_aa0 = noracepolicy*cand_white

.         
.         replace white_aa0 = 0
(294 real changes made)

.         
.         loc int "white_aa0 white_aa1 white_aa2 white_aa3 black_aa0 black_aa1 black_aa2 black_aa3"

.         
.         gen out_fair_bwdiff = out_fair_black - out_fair_white
(226 missing values generated)

.                 
.         foreach var in out_ideo_7 out_priority_sj out_fair_bwdiff       {
  2.                 loc n = subinstr("`var'", "out_", "", .)
  3.                 loc n = subinstr("`n'", "_7", "", .)
  4.                 loc n = subinstr("`n'", "priority_", "", .)
  5.                 loc n = subinstr("`n'", "_bwdiff", "", .)
  6.                 
.                 // Manually create table of differences
.                 tempname t_`n'
  7.                 tempfile tf_`n'
  8.                 postfile `t_`n'' str20 var `n'_coef `n'_se using `tf_`n''
  9.                         
.                         reg `var' `reg_sex' `reg_issues' `int' cand_age, robust
 10.                         
.                         lincom black_aa0 - white_aa0
 11.                         post `t_`n'' ("BW, No AA") (r(estimate)) (r(se))
 12.                         
.                         lincom black_aa3 - white_aa0
 13.                         post `t_`n'' ("B Cons - W No AA") (r(estimate)) (r(se))
 14.                         
.                         lincom black_aa1 - white_aa1
 15.                         post `t_`n'' ("BW, Lib") (r(estimate)) (r(se))
 16.                         
.                         lincom black_aa3 - white_aa3
 17.                         post `t_`n'' ("BW, Cons") (r(estimate)) (r(se))
 18.                 
.                 postclose `t_`n''
 19.                 
.                 preserve
 20.                         use `tf_`n'', clear
 21.                         list
 22.                                 
.                         reshape long `n'_, i(var) j(stat) s 
 23.                                 
.                         save `tf_`n'', replace
 24.                 restore 
 25.         }
note: zero_sex omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      2,339
                                                F(16, 2322)       =       3.08
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0210
                                                Root MSE          =     .26074

-------------------------------------------------------------------------------------
                    |               Robust
         out_ideo_7 | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |   .0042271   .0108417     0.39   0.697    -.0170334    .0254875
           zero_sex |          0  (omitted)
 cand_policy_abort1 |   .0815165    .017496     4.66   0.000     .0472071    .1158259
 cand_policy_abort2 |   .0381148   .0169459     2.25   0.025     .0048842    .0713454
   cand_policy_tax1 |   .0278099   .0164508     1.69   0.091    -.0044499    .0600697
   cand_policy_tax2 |  -.0039468   .0166908    -0.24   0.813    -.0366772    .0287836
cand_policy_health1 |   .0398922   .0164599     2.42   0.015     .0076145    .0721699
cand_policy_health2 |   .0361844   .0170259     2.13   0.034     .0027968    .0695719
   cand_policy_eco1 |    .011355   .0151719     0.75   0.454    -.0183969    .0411069
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          white_aa1 |   .0130188   .0223867     0.58   0.561    -.0308812    .0569188
          white_aa2 |   .0277604   .0227521     1.22   0.223     -.016856    .0723769
          white_aa3 |   .0015667   .0212611     0.07   0.941     -.040126    .0432593
          black_aa0 |   .0417546   .0212423     1.97   0.049     .0000988    .0834104
          black_aa1 |   .0691943   .0210209     3.29   0.001     .0279727    .1104159
          black_aa2 |   .0269197   .0227852     1.18   0.238    -.0177618    .0716012
          black_aa3 |   .0263299   .0217311     1.21   0.226    -.0162845    .0689443
           cand_age |  -.0009288   .0008908    -1.04   0.297    -.0026757     .000818
              _cons |   .6421046   .0523822    12.26   0.000     .5393839    .7448253
-------------------------------------------------------------------------------------

 ( 1)  - o.white_aa0 + black_aa0 = 0

------------------------------------------------------------------------------
  out_ideo_7 | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |   .0417546   .0212423     1.97   0.049     .0000988    .0834104
------------------------------------------------------------------------------

 ( 1)  - o.white_aa0 + black_aa3 = 0

------------------------------------------------------------------------------
  out_ideo_7 | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |   .0263299   .0217311     1.21   0.226    -.0162845    .0689443
------------------------------------------------------------------------------

 ( 1)  - white_aa1 + black_aa1 = 0

------------------------------------------------------------------------------
  out_ideo_7 | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |   .0561755   .0212977     2.64   0.008     .0144111      .09794
------------------------------------------------------------------------------

 ( 1)  - white_aa3 + black_aa3 = 0

------------------------------------------------------------------------------
  out_ideo_7 | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |   .0247632   .0208204     1.19   0.234    -.0160653    .0655917
------------------------------------------------------------------------------

     +----------------------------------------+
     |              var   ideo_c~f    ideo_se |
     |----------------------------------------|
  1. |        BW, No AA   .0417546   .0212423 |
  2. | B Cons - W No AA   .0263299   .0217311 |
  3. |          BW, Lib   .0561755   .0212977 |
  4. |         BW, Cons   .0247632   .0208204 |
     +----------------------------------------+
(j = coef se)

Data                               Wide   ->   Long
-----------------------------------------------------------------------------
Number of observations                4   ->   8           
Number of variables                   3   ->   3           
j variable (2 values)                     ->   stat
xij variables:
                      ideo_coef ideo_se   ->   ideo_
-----------------------------------------------------------------------------
file C:\Users\wujen\AppData\Local\Temp\ST_310c_000001.tmp saved as .dta format
note: zero_sex omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      2,237
                                                F(16, 2220)       =       2.61
                                                Prob > F          =     0.0005
                                                R-squared         =     0.0180
                                                Root MSE          =      .3518

-------------------------------------------------------------------------------------
                    |               Robust
    out_priority_sj | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |  -.0254704   .0149464    -1.70   0.089    -.0547808    .0038401
           zero_sex |          0  (omitted)
 cand_policy_abort1 |    .002989   .0233995     0.13   0.898    -.0428983    .0488762
 cand_policy_abort2 |    .011259   .0237727     0.47   0.636    -.0353599     .057878
   cand_policy_tax1 |   .0243487   .0236005     1.03   0.302    -.0219326    .0706301
   cand_policy_tax2 |   .0187225   .0231288     0.81   0.418    -.0266338    .0640788
cand_policy_health1 |   .0122916   .0228099     0.54   0.590    -.0324394    .0570226
cand_policy_health2 |   .0170047   .0242816     0.70   0.484    -.0306124    .0646218
   cand_policy_eco1 |   .0341733   .0212082     1.61   0.107    -.0074166    .0757633
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          white_aa1 |   .0598439   .0305666     1.96   0.050    -.0000982     .119786
          white_aa2 |   .0715095   .0310534     2.30   0.021     .0106128    .1324063
          white_aa3 |   .0403596   .0291768     1.38   0.167    -.0168571    .0975764
          black_aa0 |   .0298594   .0298884     1.00   0.318    -.0287528    .0884716
          black_aa1 |   .1414099   .0292767     4.83   0.000     .0839973    .1988224
          black_aa2 |   .0855879    .030291     2.83   0.005     .0261861    .1449896
          black_aa3 |   .1118929   .0291026     3.84   0.000     .0548217    .1689641
           cand_age |   .0014646   .0012258     1.19   0.232    -.0009392    .0038683
              _cons |    .488685   .0727609     6.72   0.000     .3459985    .6313716
-------------------------------------------------------------------------------------

 ( 1)  - o.white_aa0 + black_aa0 = 0

------------------------------------------------------------------------------
out_priori~j | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |   .0298594   .0298884     1.00   0.318    -.0287528    .0884716
------------------------------------------------------------------------------

 ( 1)  - o.white_aa0 + black_aa3 = 0

------------------------------------------------------------------------------
out_priori~j | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |   .1118929   .0291026     3.84   0.000     .0548217    .1689641
------------------------------------------------------------------------------

 ( 1)  - white_aa1 + black_aa1 = 0

------------------------------------------------------------------------------
out_priori~j | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |    .081566   .0299239     2.73   0.006     .0228842    .1402477
------------------------------------------------------------------------------

 ( 1)  - white_aa3 + black_aa3 = 0

------------------------------------------------------------------------------
out_priori~j | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |   .0715333   .0283282     2.53   0.012     .0159807    .1270858
------------------------------------------------------------------------------

     +----------------------------------------+
     |              var    sj_coef      sj_se |
     |----------------------------------------|
  1. |        BW, No AA   .0298594   .0298884 |
  2. | B Cons - W No AA   .1118929   .0291026 |
  3. |          BW, Lib    .081566   .0299239 |
  4. |         BW, Cons   .0715332   .0283282 |
     +----------------------------------------+
(j = coef se)

Data                               Wide   ->   Long
-----------------------------------------------------------------------------
Number of observations                4   ->   8           
Number of variables                   3   ->   3           
j variable (2 values)                     ->   stat
xij variables:
                          sj_coef sj_se   ->   sj_
-----------------------------------------------------------------------------
file C:\Users\wujen\AppData\Local\Temp\ST_310c_000003.tmp saved as .dta format
note: zero_sex omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      2,241
                                                F(16, 2224)       =       4.58
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0313
                                                Root MSE          =      .3793

-------------------------------------------------------------------------------------
                    |               Robust
    out_fair_bwdiff | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |   .0321077   .0160745     2.00   0.046     .0005852    .0636303
           zero_sex |          0  (omitted)
 cand_policy_abort1 |   .0086124   .0256202     0.34   0.737    -.0416296    .0588544
 cand_policy_abort2 |   .0013976    .024918     0.06   0.955    -.0474673    .0502626
   cand_policy_tax1 |   .0146129   .0250636     0.58   0.560    -.0345376    .0637633
   cand_policy_tax2 |   .0290748   .0237573     1.22   0.221    -.0175141    .0756637
cand_policy_health1 |   .0294106   .0239024     1.23   0.219    -.0174629     .076284
cand_policy_health2 |   .0346009   .0274645     1.26   0.208    -.0192579    .0884598
   cand_policy_eco1 |   .0430522   .0230167     1.87   0.062    -.0020842    .0881887
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          white_aa1 |   .0909294   .0323785     2.81   0.005     .0274342    .1544246
          white_aa2 |   .0759166   .0326236     2.33   0.020     .0119407    .1398926
          white_aa3 |  -.0207179   .0302376    -0.69   0.493    -.0800147    .0385789
          black_aa0 |   .0964004   .0298165     3.23   0.001     .0379293    .1548715
          black_aa1 |   .1717674   .0315848     5.44   0.000     .1098286    .2337061
          black_aa2 |   .1516686   .0329466     4.60   0.000     .0870592     .216278
          black_aa3 |   .1130105   .0305455     3.70   0.000     .0531098    .1729112
           cand_age |   .0004088   .0013256     0.31   0.758    -.0021908    .0030084
              _cons |  -.0799885   .0770036    -1.04   0.299    -.2309949     .071018
-------------------------------------------------------------------------------------

 ( 1)  - o.white_aa0 + black_aa0 = 0

------------------------------------------------------------------------------
out_fair_b~f | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |   .0964004   .0298165     3.23   0.001     .0379293    .1548715
------------------------------------------------------------------------------

 ( 1)  - o.white_aa0 + black_aa3 = 0

------------------------------------------------------------------------------
out_fair_b~f | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |   .1130105   .0305455     3.70   0.000     .0531098    .1729112
------------------------------------------------------------------------------

 ( 1)  - white_aa1 + black_aa1 = 0

------------------------------------------------------------------------------
out_fair_b~f | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |    .080838    .033563     2.41   0.016     .0150199     .146656
------------------------------------------------------------------------------

 ( 1)  - white_aa3 + black_aa3 = 0

------------------------------------------------------------------------------
out_fair_b~f | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |   .1337284   .0304394     4.39   0.000     .0740357     .193421
------------------------------------------------------------------------------

     +----------------------------------------+
     |              var   fair_c~f    fair_se |
     |----------------------------------------|
  1. |        BW, No AA   .0964004   .0298165 |
  2. | B Cons - W No AA   .1130105   .0305455 |
  3. |          BW, Lib    .080838    .033563 |
  4. |         BW, Cons   .1337284   .0304394 |
     +----------------------------------------+
(j = coef se)

Data                               Wide   ->   Long
-----------------------------------------------------------------------------
Number of observations                4   ->   8           
Number of variables                   3   ->   3           
j variable (2 values)                     ->   stat
xij variables:
                      fair_coef fair_se   ->   fair_
-----------------------------------------------------------------------------
file C:\Users\wujen\AppData\Local\Temp\ST_310c_000005.tmp saved as .dta format

. 
.         use `tf_ideo', clear

.         
.         cap drop _m

.         merge 1:1 var stat using `tf_sj'

    Result                      Number of obs
    -----------------------------------------
    Not matched                             0
    Matched                                 8  (_merge==3)
    -----------------------------------------

.         drop _m

.         merge 1:1 var stat using `tf_fair'

    Result                      Number of obs
    -----------------------------------------
    Not matched                             0
    Matched                                 8  (_merge==3)
    -----------------------------------------

.         drop _m

.         list

     +----------------------------------------------------------+
     |              var   stat      ideo_        sj_      fair_ |
     |----------------------------------------------------------|
  1. | B Cons - W No AA   coef   .0263299   .1118929   .1130105 |
  2. | B Cons - W No AA     se   .0217311   .0291026   .0305455 |
  3. |         BW, Cons   coef   .0247632   .0715332   .1337284 |
  4. |         BW, Cons     se   .0208204   .0283282   .0304394 |
  5. |          BW, Lib   coef   .0561755    .081566    .080838 |
     |----------------------------------------------------------|
  6. |          BW, Lib     se   .0212977   .0299239    .033563 |
  7. |        BW, No AA   coef   .0417546   .0298594   .0964004 |
  8. |        BW, No AA     se   .0212423   .0298884   .0298165 |
     +----------------------------------------------------------+

.         
.         foreach v in ideo sj fair {
  2.                 gen `v' = "0"+string(round(`v'_, 0.002))
  3.                 replace `v' = subinstr(`v', "-","", .)
  4.                 replace `v' = "-"+`v' if substr(string(`v'_), 1, 1) == "-"
  5.                 
.                 drop `v'_
  6.         }
(0 real changes made)
(0 real changes made)
(0 real changes made)
(0 real changes made)
(0 real changes made)
(0 real changes made)

.         
.         gen order = . 
(8 missing values generated)

.         replace order = 1 if var == "BW, No AA"
(2 real changes made)

.         replace order = 2 if var == "B Cons - W No AA"
(2 real changes made)

.         replace order = 3 if var == "BW, Cons"
(2 real changes made)

.         replace order = 4 if var == "BW, Lib"
(2 real changes made)

.         replace order = order + 0.5 if stat == "se"
(4 real changes made)

.         sort order

.         
.         
.         gen varname = ""
(8 missing values generated)

.         replace varname = "Black - White, No Position" if order == 1
variable varname was str1 now str26
(1 real change made)

.         replace varname = "Back, Replace - White, No Position" if order == 2
variable varname was str26 now str34
(1 real change made)

.         replace varname = "Black - White, Replace" if order == 3
(1 real change made)

.         replace varname = "Black - White, Expand" if order == 4
(1 real change made)

.         
.         drop order var 

.         order var stat varname ideo sj fair

.         list

     +-------------------------------------------------------------------+
     |                            varname   stat    ideo      sj    fair |
     |-------------------------------------------------------------------|
  1. |         Black - White, No Position   coef   0.042    0.03   0.096 |
  2. |                                        se   0.022    0.03    0.03 |
  3. | Back, Replace - White, No Position   coef   0.026   0.112   0.114 |
  4. |                                        se   0.022    0.03    0.03 |
  5. |             Black - White, Replace   coef   0.024   0.072   0.134 |
     |-------------------------------------------------------------------|
  6. |                                        se    0.02   0.028    0.03 |
  7. |              Black - White, Expand   coef   0.056   0.082    0.08 |
  8. |                                        se   0.022    0.03   0.034 |
     +-------------------------------------------------------------------+

.         
.         outsheet using table_3.csv, comma replace
(file table_3.csv not found)

.                 
.         
. 
. 
. // Study 2
.         use data_study_2.dta, clear

. 
. 
. // Set omitted categories
.         gen zero_race = 0

.         label var zero_race "White"

.         gen zero_sex = 0

.         label var zero_sex "Male"

.         gen zero_eco = 0

.         label var zero_eco "Maintain investment in energy"

.         gen zero_biden = 0

.         label var zero_biden "Vote Share: 51%"

.         gen zero_exp = 0

.         label var zero_exp "Political newcomer"

.         gen zero_dist = 0

.         label var zero_dist "[63, 8, 13, 11, 5]"

.         gen zero_racepol = 0

.         label var zero_racepol "Not shown policy"

.         
. // Set regression variables
.         loc reg_race "cand_black zero_race cand_asian cand_hispa"

.         loc reg_sex "cand_female zero_sex"

.         loc reg_exp "cand_exp_teach cand_exp_council cand_exp_lawyer cand_exp_business zero_exp"

.         loc reg_biden "cand_biden_p59 cand_biden_p57 cand_biden_p55 cand_biden_p53 zero_biden"

.         loc reg_distpop "cand_dist1 cand_dist2 cand_dist3 cand_dist4 cand_dist5 cand_dist6 zero_dist"

.         loc reg_issues "cand_policy_abort1 cand_policy_abort2 cand_policy_tax1 cand_policy_tax2"

.         loc reg_issues "`reg_issues' cand_policy_health1 cand_policy_health2 cand_policy_eco1 zero_eco"

.         loc reg_affirm "cand_policy_aa1 cand_policy_aa2 cand_policy_aa3 zero_racepol"

.         loc reg_affirm2 "noracepolicy cand_policy_aa1 cand_policy_aa2 cand_policy_aa3 "

.         
. // Interactive Terms for Black Candidate X Affirmative Action
.         gen noracepolicy = cand_policy_aa1 == 0 & cand_policy_aa2 == 0 & cand_policy_aa3 == 0   

.         
.         loc int ""

.         foreach r in white black asian hispa {
  2.                 gen `r'_aa1 = cand_policy_aa1*cand_`r'
  3.                 gen `r'_aa2 = cand_policy_aa2*cand_`r'
  4.                 gen `r'_aa3 = cand_policy_aa3*cand_`r'
  5.                 gen `r'_aa0 = noracepolicy*cand_`r'
  6.                         
.                 loc int "`int' `r'_aa0 `r'_aa1 `r'_aa2 `r'_aa3"
  7.         
.         }

.         // set reference
.         replace white_aa0 = 0
(560 real changes made)

.         
.         gen out_fair_bwdiff = out_fair_black - out_fair_white
(2 missing values generated)

.         
.                 
. //============================================================================== Regress the things
. 
.         // Ideology
.         tempname temp

.         tempfile tempf

.         postfile `temp' str20 var ideo_coef ideo_se using `tempf'

.         forvalues var = 0/3 {
  2.                 reg out_ideo `reg_sex' `reg_exp' `reg_biden' `reg_distpop' `reg_issues' `int' ///
>                         cand_age, vce(cluster r_id)
  3.                 
.                 lincom _cons + black_aa`var' 
  4.                 post `temp' ("black_aa`var'") (r(estimate)) (r(se))
  5.                 
.                 lincom _cons + white_aa`var' 
  6.                 post `temp' ("white_aa`var'") (r(estimate)) (r(se))
  7.                 
.         }
note: zero_sex omitted because of collinearity.
note: zero_exp omitted because of collinearity.
note: zero_biden omitted because of collinearity.
note: zero_dist omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      7,230
                                                F(38, 1446)       =       7.00
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0371
                                                Root MSE          =     .23868

                                      (Std. err. adjusted for 1,447 clusters in r_id)
-------------------------------------------------------------------------------------
                    |               Robust
           out_ideo | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |   .0059291   .0046498     1.28   0.202     -.003192    .0150501
           zero_sex |          0  (omitted)
     cand_exp_teach |   .0122159   .0065721     1.86   0.063    -.0006761    .0251078
   cand_exp_council |   .0051068   .0064179     0.80   0.426    -.0074826    .0176962
    cand_exp_lawyer |   .0030542   .0066661     0.46   0.647    -.0100221    .0161305
  cand_exp_business |   .0055399   .0065377     0.85   0.397    -.0072845    .0183642
           zero_exp |          0  (omitted)
     cand_biden_p59 |   .0000409   .0066104     0.01   0.995    -.0129261    .0130079
     cand_biden_p57 |   .0103569   .0066061     1.57   0.117    -.0026016    .0233154
     cand_biden_p55 |   .0030348   .0064071     0.47   0.636    -.0095334     .015603
     cand_biden_p53 |   .0030762   .0063017     0.49   0.626    -.0092852    .0154376
         zero_biden |          0  (omitted)
         cand_dist1 |  -.0113719   .0085274    -1.33   0.183    -.0280992    .0053555
         cand_dist2 |  -.0093389   .0083509    -1.12   0.264    -.0257201    .0070422
         cand_dist3 |  -.0159317   .0086303    -1.85   0.065     -.032861    .0009976
         cand_dist4 |  -.0078922   .0086635    -0.91   0.362    -.0248866    .0091022
         cand_dist5 |  -.0150726   .0089194    -1.69   0.091    -.0325689    .0024237
         cand_dist6 |  -.0179895   .0085356    -2.11   0.035    -.0347331   -.0012459
          zero_dist |          0  (omitted)
 cand_policy_abort1 |   .0865966   .0093206     9.29   0.000     .0683133    .1048799
 cand_policy_abort2 |   .0222603   .0085781     2.60   0.010     .0054334    .0390871
   cand_policy_tax1 |   .0099431   .0091723     1.08   0.279    -.0080493    .0279355
   cand_policy_tax2 |  -.0153925    .008837    -1.74   0.082    -.0327271    .0019421
cand_policy_health1 |   .0336736   .0088891     3.79   0.000     .0162367    .0511104
cand_policy_health2 |   .0063585   .0087873     0.72   0.469    -.0108788    .0235958
   cand_policy_eco1 |   .0132894   .0076099     1.75   0.081    -.0016382    .0282169
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          white_aa1 |   .0139106   .0144716     0.96   0.337     -.014477    .0422983
          white_aa2 |   .0115353   .0148021     0.78   0.436    -.0175006    .0405711
          white_aa3 |  -.0613646   .0146132    -4.20   0.000      -.09003   -.0326992
          black_aa0 |   -.005849   .0135541    -0.43   0.666    -.0324368    .0207389
          black_aa1 |   .0312423   .0134733     2.32   0.021     .0048129    .0576716
          black_aa2 |   .0155517    .014348     1.08   0.279    -.0125934    .0436968
          black_aa3 |   -.039669    .013763    -2.88   0.004    -.0666666   -.0126714
          asian_aa0 |   -.019575   .0149818    -1.31   0.192    -.0489633    .0098133
          asian_aa1 |   .0104106   .0151699     0.69   0.493    -.0193468    .0401679
          asian_aa2 |    .022626   .0151685     1.49   0.136    -.0071287    .0523807
          asian_aa3 |  -.0413389   .0147379    -2.80   0.005     -.070249   -.0124289
          hispa_aa0 |   .0032418   .0142965     0.23   0.821    -.0248022    .0312859
          hispa_aa1 |   .0261759   .0154693     1.69   0.091    -.0041688    .0565206
          hispa_aa2 |   .0247045    .014716     1.68   0.093    -.0041625    .0535714
          hispa_aa3 |  -.0491622   .0158941    -3.09   0.002    -.0803401   -.0179842
           cand_age |  -.0007007   .0004648    -1.51   0.132    -.0016124     .000211
              _cons |   .6851087    .028839    23.76   0.000     .6285379    .7416796
-------------------------------------------------------------------------------------

 ( 1)  black_aa0 + _cons = 0

------------------------------------------------------------------------------
    out_ideo | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |   .6792598   .0289285    23.48   0.000     .6225134    .7360061
------------------------------------------------------------------------------

 ( 1)  o.white_aa0 + _cons = 0

------------------------------------------------------------------------------
    out_ideo | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |   .6851087    .028839    23.76   0.000     .6285379    .7416796
------------------------------------------------------------------------------
note: zero_sex omitted because of collinearity.
note: zero_exp omitted because of collinearity.
note: zero_biden omitted because of collinearity.
note: zero_dist omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      7,230
                                                F(38, 1446)       =       7.00
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0371
                                                Root MSE          =     .23868

                                      (Std. err. adjusted for 1,447 clusters in r_id)
-------------------------------------------------------------------------------------
                    |               Robust
           out_ideo | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |   .0059291   .0046498     1.28   0.202     -.003192    .0150501
           zero_sex |          0  (omitted)
     cand_exp_teach |   .0122159   .0065721     1.86   0.063    -.0006761    .0251078
   cand_exp_council |   .0051068   .0064179     0.80   0.426    -.0074826    .0176962
    cand_exp_lawyer |   .0030542   .0066661     0.46   0.647    -.0100221    .0161305
  cand_exp_business |   .0055399   .0065377     0.85   0.397    -.0072845    .0183642
           zero_exp |          0  (omitted)
     cand_biden_p59 |   .0000409   .0066104     0.01   0.995    -.0129261    .0130079
     cand_biden_p57 |   .0103569   .0066061     1.57   0.117    -.0026016    .0233154
     cand_biden_p55 |   .0030348   .0064071     0.47   0.636    -.0095334     .015603
     cand_biden_p53 |   .0030762   .0063017     0.49   0.626    -.0092852    .0154376
         zero_biden |          0  (omitted)
         cand_dist1 |  -.0113719   .0085274    -1.33   0.183    -.0280992    .0053555
         cand_dist2 |  -.0093389   .0083509    -1.12   0.264    -.0257201    .0070422
         cand_dist3 |  -.0159317   .0086303    -1.85   0.065     -.032861    .0009976
         cand_dist4 |  -.0078922   .0086635    -0.91   0.362    -.0248866    .0091022
         cand_dist5 |  -.0150726   .0089194    -1.69   0.091    -.0325689    .0024237
         cand_dist6 |  -.0179895   .0085356    -2.11   0.035    -.0347331   -.0012459
          zero_dist |          0  (omitted)
 cand_policy_abort1 |   .0865966   .0093206     9.29   0.000     .0683133    .1048799
 cand_policy_abort2 |   .0222603   .0085781     2.60   0.010     .0054334    .0390871
   cand_policy_tax1 |   .0099431   .0091723     1.08   0.279    -.0080493    .0279355
   cand_policy_tax2 |  -.0153925    .008837    -1.74   0.082    -.0327271    .0019421
cand_policy_health1 |   .0336736   .0088891     3.79   0.000     .0162367    .0511104
cand_policy_health2 |   .0063585   .0087873     0.72   0.469    -.0108788    .0235958
   cand_policy_eco1 |   .0132894   .0076099     1.75   0.081    -.0016382    .0282169
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          white_aa1 |   .0139106   .0144716     0.96   0.337     -.014477    .0422983
          white_aa2 |   .0115353   .0148021     0.78   0.436    -.0175006    .0405711
          white_aa3 |  -.0613646   .0146132    -4.20   0.000      -.09003   -.0326992
          black_aa0 |   -.005849   .0135541    -0.43   0.666    -.0324368    .0207389
          black_aa1 |   .0312423   .0134733     2.32   0.021     .0048129    .0576716
          black_aa2 |   .0155517    .014348     1.08   0.279    -.0125934    .0436968
          black_aa3 |   -.039669    .013763    -2.88   0.004    -.0666666   -.0126714
          asian_aa0 |   -.019575   .0149818    -1.31   0.192    -.0489633    .0098133
          asian_aa1 |   .0104106   .0151699     0.69   0.493    -.0193468    .0401679
          asian_aa2 |    .022626   .0151685     1.49   0.136    -.0071287    .0523807
          asian_aa3 |  -.0413389   .0147379    -2.80   0.005     -.070249   -.0124289
          hispa_aa0 |   .0032418   .0142965     0.23   0.821    -.0248022    .0312859
          hispa_aa1 |   .0261759   .0154693     1.69   0.091    -.0041688    .0565206
          hispa_aa2 |   .0247045    .014716     1.68   0.093    -.0041625    .0535714
          hispa_aa3 |  -.0491622   .0158941    -3.09   0.002    -.0803401   -.0179842
           cand_age |  -.0007007   .0004648    -1.51   0.132    -.0016124     .000211
              _cons |   .6851087    .028839    23.76   0.000     .6285379    .7416796
-------------------------------------------------------------------------------------

 ( 1)  black_aa1 + _cons = 0

------------------------------------------------------------------------------
    out_ideo | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |    .716351   .0285184    25.12   0.000     .6604091    .7722929
------------------------------------------------------------------------------

 ( 1)  white_aa1 + _cons = 0

------------------------------------------------------------------------------
    out_ideo | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |   .6990194   .0289928    24.11   0.000      .642147    .7558917
------------------------------------------------------------------------------
note: zero_sex omitted because of collinearity.
note: zero_exp omitted because of collinearity.
note: zero_biden omitted because of collinearity.
note: zero_dist omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      7,230
                                                F(38, 1446)       =       7.00
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0371
                                                Root MSE          =     .23868

                                      (Std. err. adjusted for 1,447 clusters in r_id)
-------------------------------------------------------------------------------------
                    |               Robust
           out_ideo | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |   .0059291   .0046498     1.28   0.202     -.003192    .0150501
           zero_sex |          0  (omitted)
     cand_exp_teach |   .0122159   .0065721     1.86   0.063    -.0006761    .0251078
   cand_exp_council |   .0051068   .0064179     0.80   0.426    -.0074826    .0176962
    cand_exp_lawyer |   .0030542   .0066661     0.46   0.647    -.0100221    .0161305
  cand_exp_business |   .0055399   .0065377     0.85   0.397    -.0072845    .0183642
           zero_exp |          0  (omitted)
     cand_biden_p59 |   .0000409   .0066104     0.01   0.995    -.0129261    .0130079
     cand_biden_p57 |   .0103569   .0066061     1.57   0.117    -.0026016    .0233154
     cand_biden_p55 |   .0030348   .0064071     0.47   0.636    -.0095334     .015603
     cand_biden_p53 |   .0030762   .0063017     0.49   0.626    -.0092852    .0154376
         zero_biden |          0  (omitted)
         cand_dist1 |  -.0113719   .0085274    -1.33   0.183    -.0280992    .0053555
         cand_dist2 |  -.0093389   .0083509    -1.12   0.264    -.0257201    .0070422
         cand_dist3 |  -.0159317   .0086303    -1.85   0.065     -.032861    .0009976
         cand_dist4 |  -.0078922   .0086635    -0.91   0.362    -.0248866    .0091022
         cand_dist5 |  -.0150726   .0089194    -1.69   0.091    -.0325689    .0024237
         cand_dist6 |  -.0179895   .0085356    -2.11   0.035    -.0347331   -.0012459
          zero_dist |          0  (omitted)
 cand_policy_abort1 |   .0865966   .0093206     9.29   0.000     .0683133    .1048799
 cand_policy_abort2 |   .0222603   .0085781     2.60   0.010     .0054334    .0390871
   cand_policy_tax1 |   .0099431   .0091723     1.08   0.279    -.0080493    .0279355
   cand_policy_tax2 |  -.0153925    .008837    -1.74   0.082    -.0327271    .0019421
cand_policy_health1 |   .0336736   .0088891     3.79   0.000     .0162367    .0511104
cand_policy_health2 |   .0063585   .0087873     0.72   0.469    -.0108788    .0235958
   cand_policy_eco1 |   .0132894   .0076099     1.75   0.081    -.0016382    .0282169
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          white_aa1 |   .0139106   .0144716     0.96   0.337     -.014477    .0422983
          white_aa2 |   .0115353   .0148021     0.78   0.436    -.0175006    .0405711
          white_aa3 |  -.0613646   .0146132    -4.20   0.000      -.09003   -.0326992
          black_aa0 |   -.005849   .0135541    -0.43   0.666    -.0324368    .0207389
          black_aa1 |   .0312423   .0134733     2.32   0.021     .0048129    .0576716
          black_aa2 |   .0155517    .014348     1.08   0.279    -.0125934    .0436968
          black_aa3 |   -.039669    .013763    -2.88   0.004    -.0666666   -.0126714
          asian_aa0 |   -.019575   .0149818    -1.31   0.192    -.0489633    .0098133
          asian_aa1 |   .0104106   .0151699     0.69   0.493    -.0193468    .0401679
          asian_aa2 |    .022626   .0151685     1.49   0.136    -.0071287    .0523807
          asian_aa3 |  -.0413389   .0147379    -2.80   0.005     -.070249   -.0124289
          hispa_aa0 |   .0032418   .0142965     0.23   0.821    -.0248022    .0312859
          hispa_aa1 |   .0261759   .0154693     1.69   0.091    -.0041688    .0565206
          hispa_aa2 |   .0247045    .014716     1.68   0.093    -.0041625    .0535714
          hispa_aa3 |  -.0491622   .0158941    -3.09   0.002    -.0803401   -.0179842
           cand_age |  -.0007007   .0004648    -1.51   0.132    -.0016124     .000211
              _cons |   .6851087    .028839    23.76   0.000     .6285379    .7416796
-------------------------------------------------------------------------------------

 ( 1)  black_aa2 + _cons = 0

------------------------------------------------------------------------------
    out_ideo | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |   .7006605   .0287388    24.38   0.000     .6442862    .7570347
------------------------------------------------------------------------------

 ( 1)  white_aa2 + _cons = 0

------------------------------------------------------------------------------
    out_ideo | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |    .696644   .0289795    24.04   0.000     .6397977    .7534904
------------------------------------------------------------------------------
note: zero_sex omitted because of collinearity.
note: zero_exp omitted because of collinearity.
note: zero_biden omitted because of collinearity.
note: zero_dist omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      7,230
                                                F(38, 1446)       =       7.00
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0371
                                                Root MSE          =     .23868

                                      (Std. err. adjusted for 1,447 clusters in r_id)
-------------------------------------------------------------------------------------
                    |               Robust
           out_ideo | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |   .0059291   .0046498     1.28   0.202     -.003192    .0150501
           zero_sex |          0  (omitted)
     cand_exp_teach |   .0122159   .0065721     1.86   0.063    -.0006761    .0251078
   cand_exp_council |   .0051068   .0064179     0.80   0.426    -.0074826    .0176962
    cand_exp_lawyer |   .0030542   .0066661     0.46   0.647    -.0100221    .0161305
  cand_exp_business |   .0055399   .0065377     0.85   0.397    -.0072845    .0183642
           zero_exp |          0  (omitted)
     cand_biden_p59 |   .0000409   .0066104     0.01   0.995    -.0129261    .0130079
     cand_biden_p57 |   .0103569   .0066061     1.57   0.117    -.0026016    .0233154
     cand_biden_p55 |   .0030348   .0064071     0.47   0.636    -.0095334     .015603
     cand_biden_p53 |   .0030762   .0063017     0.49   0.626    -.0092852    .0154376
         zero_biden |          0  (omitted)
         cand_dist1 |  -.0113719   .0085274    -1.33   0.183    -.0280992    .0053555
         cand_dist2 |  -.0093389   .0083509    -1.12   0.264    -.0257201    .0070422
         cand_dist3 |  -.0159317   .0086303    -1.85   0.065     -.032861    .0009976
         cand_dist4 |  -.0078922   .0086635    -0.91   0.362    -.0248866    .0091022
         cand_dist5 |  -.0150726   .0089194    -1.69   0.091    -.0325689    .0024237
         cand_dist6 |  -.0179895   .0085356    -2.11   0.035    -.0347331   -.0012459
          zero_dist |          0  (omitted)
 cand_policy_abort1 |   .0865966   .0093206     9.29   0.000     .0683133    .1048799
 cand_policy_abort2 |   .0222603   .0085781     2.60   0.010     .0054334    .0390871
   cand_policy_tax1 |   .0099431   .0091723     1.08   0.279    -.0080493    .0279355
   cand_policy_tax2 |  -.0153925    .008837    -1.74   0.082    -.0327271    .0019421
cand_policy_health1 |   .0336736   .0088891     3.79   0.000     .0162367    .0511104
cand_policy_health2 |   .0063585   .0087873     0.72   0.469    -.0108788    .0235958
   cand_policy_eco1 |   .0132894   .0076099     1.75   0.081    -.0016382    .0282169
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          white_aa1 |   .0139106   .0144716     0.96   0.337     -.014477    .0422983
          white_aa2 |   .0115353   .0148021     0.78   0.436    -.0175006    .0405711
          white_aa3 |  -.0613646   .0146132    -4.20   0.000      -.09003   -.0326992
          black_aa0 |   -.005849   .0135541    -0.43   0.666    -.0324368    .0207389
          black_aa1 |   .0312423   .0134733     2.32   0.021     .0048129    .0576716
          black_aa2 |   .0155517    .014348     1.08   0.279    -.0125934    .0436968
          black_aa3 |   -.039669    .013763    -2.88   0.004    -.0666666   -.0126714
          asian_aa0 |   -.019575   .0149818    -1.31   0.192    -.0489633    .0098133
          asian_aa1 |   .0104106   .0151699     0.69   0.493    -.0193468    .0401679
          asian_aa2 |    .022626   .0151685     1.49   0.136    -.0071287    .0523807
          asian_aa3 |  -.0413389   .0147379    -2.80   0.005     -.070249   -.0124289
          hispa_aa0 |   .0032418   .0142965     0.23   0.821    -.0248022    .0312859
          hispa_aa1 |   .0261759   .0154693     1.69   0.091    -.0041688    .0565206
          hispa_aa2 |   .0247045    .014716     1.68   0.093    -.0041625    .0535714
          hispa_aa3 |  -.0491622   .0158941    -3.09   0.002    -.0803401   -.0179842
           cand_age |  -.0007007   .0004648    -1.51   0.132    -.0016124     .000211
              _cons |   .6851087    .028839    23.76   0.000     .6285379    .7416796
-------------------------------------------------------------------------------------

 ( 1)  black_aa3 + _cons = 0

------------------------------------------------------------------------------
    out_ideo | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |   .6454397   .0298079    21.65   0.000     .5869683    .7039111
------------------------------------------------------------------------------

 ( 1)  white_aa3 + _cons = 0

------------------------------------------------------------------------------
    out_ideo | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |   .6237442   .0287787    21.67   0.000     .5672917    .6801966
------------------------------------------------------------------------------

.                 postclose `temp'

.         preserve        

.                 use `tempf', clear

.                 list

     +---------------------------------+
     |       var   ideo_c~f    ideo_se |
     |---------------------------------|
  1. | black_aa0   .6792598   .0289285 |
  2. | white_aa0   .6851087    .028839 |
  3. | black_aa1    .716351   .0285184 |
  4. | white_aa1   .6990194   .0289928 |
  5. | black_aa2   .7006605   .0287388 |
     |---------------------------------|
  6. | white_aa2    .696644   .0289795 |
  7. | black_aa3   .6454397   .0298079 |
  8. | white_aa3   .6237442   .0287787 |
     +---------------------------------+

.                 
.                 reshape long ideo_, i(var) j(stat) s 
(j = coef se)

Data                               Wide   ->   Long
-----------------------------------------------------------------------------
Number of observations                8   ->   16          
Number of variables                   3   ->   3           
j variable (2 values)                     ->   stat
xij variables:
                      ideo_coef ideo_se   ->   ideo_
-----------------------------------------------------------------------------

.                 
.                 save `tempf', replace
file C:\Users\wujen\AppData\Local\Temp\ST_310c_000007.tmp saved as .dta format

.         restore

.         
.         // Fairness
.         tempname temp2

.         tempfile tempf2

.         postfile `temp2' str20 var favor_coef favor_se using `tempf2'

.         forvalues var = 0/3 {
  2.                 reg out_fair_bwdiff `reg_sex' `reg_exp' `reg_biden' `reg_distpop' `reg_issues' `int' 
> ///
>                         cand_age, vce(cluster r_id)
  3.                 
.                 lincom _cons + black_aa`var' 
  4.                 post `temp2' ("black_aa`var'") (r(estimate)) (r(se))
  5.                 
.                 lincom _cons + white_aa`var' 
  6.                 post `temp2' ("white_aa`var'") (r(estimate)) (r(se))
  7.                 
.         }
note: zero_sex omitted because of collinearity.
note: zero_exp omitted because of collinearity.
note: zero_biden omitted because of collinearity.
note: zero_dist omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      7,233
                                                F(38, 1446)       =      10.79
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0662
                                                Root MSE          =     .37231

                                      (Std. err. adjusted for 1,447 clusters in r_id)
-------------------------------------------------------------------------------------
                    |               Robust
    out_fair_bwdiff | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |   .0139265   .0076268     1.83   0.068    -.0010342    .0288872
           zero_sex |          0  (omitted)
     cand_exp_teach |  -.0112882   .0112302    -1.01   0.315    -.0333175     .010741
   cand_exp_council |   .0049001   .0112728     0.43   0.664    -.0172127     .027013
    cand_exp_lawyer |   -.010402   .0117992    -0.88   0.378    -.0335474    .0127434
  cand_exp_business |  -.0089442   .0113374    -0.79   0.430    -.0311838    .0132954
           zero_exp |          0  (omitted)
     cand_biden_p59 |   .0079005   .0116374     0.68   0.497    -.0149274    .0307284
     cand_biden_p57 |    .002314   .0112995     0.20   0.838    -.0198512    .0244792
     cand_biden_p55 |    .020527   .0117194     1.75   0.080    -.0024619    .0435159
     cand_biden_p53 |   .0122306   .0114134     1.07   0.284    -.0101581    .0346192
         zero_biden |          0  (omitted)
         cand_dist1 |   .0470683   .0146007     3.22   0.001     .0184276    .0757091
         cand_dist2 |   .0742289   .0150229     4.94   0.000     .0447599     .103698
         cand_dist3 |    .084251   .0159216     5.29   0.000     .0530191    .1154828
         cand_dist4 |   .0287881   .0144329     1.99   0.046     .0004764    .0570997
         cand_dist5 |   .0064837   .0150236     0.43   0.666    -.0229867    .0359542
         cand_dist6 |   .0183777   .0143633     1.28   0.201    -.0097974    .0465528
          zero_dist |          0  (omitted)
 cand_policy_abort1 |    .015618   .0136396     1.15   0.252    -.0111375    .0423735
 cand_policy_abort2 |   .0051392   .0130142     0.39   0.693    -.0203895     .030668
   cand_policy_tax1 |   .0252993   .0134408     1.88   0.060    -.0010662    .0516647
   cand_policy_tax2 |   .0194576   .0132096     1.47   0.141    -.0064544    .0453697
cand_policy_health1 |    .015918   .0133605     1.19   0.234    -.0102901    .0421262
cand_policy_health2 |   .0239248   .0133908     1.79   0.074    -.0023428    .0501923
   cand_policy_eco1 |   .0220292   .0121881     1.81   0.071     -.001879    .0459373
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          white_aa1 |   .0467187   .0229738     2.03   0.042     .0016532    .0917842
          white_aa2 |   .0410289   .0231961     1.77   0.077    -.0044727    .0865304
          white_aa3 |  -.1027482   .0221974    -4.63   0.000    -.1462908   -.0592056
          black_aa0 |   .1868773    .022748     8.22   0.000     .1422546       .2315
          black_aa1 |   .2470242   .0230655    10.71   0.000     .2017789    .2922696
          black_aa2 |   .2276338   .0230118     9.89   0.000     .1824938    .2727738
          black_aa3 |   .1179799   .0222085     5.31   0.000     .0744156    .1615442
          asian_aa0 |   .0384585   .0216096     1.78   0.075     -.003931     .080848
          asian_aa1 |    .095862   .0233697     4.10   0.000     .0500199    .1417041
          asian_aa2 |   .1096244   .0230638     4.75   0.000     .0643822    .1548665
          asian_aa3 |   .0160585   .0221627     0.72   0.469    -.0274159     .059533
          hispa_aa0 |   .0634578   .0200615     3.16   0.002     .0241051    .1028104
          hispa_aa1 |   .1206673   .0236912     5.09   0.000     .0741945    .1671401
          hispa_aa2 |   .1046724   .0233395     4.48   0.000     .0588895    .1504552
          hispa_aa3 |    .004609   .0228092     0.20   0.840    -.0401336    .0493517
           cand_age |  -.0000902   .0007096    -0.13   0.899    -.0014822    .0013017
              _cons |   -.068754   .0444104    -1.55   0.122    -.1558697    .0183617
-------------------------------------------------------------------------------------

 ( 1)  black_aa0 + _cons = 0

------------------------------------------------------------------------------
out_fair_b~f | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |   .1181233   .0446224     2.65   0.008     .0305918    .2056548
------------------------------------------------------------------------------

 ( 1)  o.white_aa0 + _cons = 0

------------------------------------------------------------------------------
out_fair_b~f | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |   -.068754   .0444104    -1.55   0.122    -.1558697    .0183617
------------------------------------------------------------------------------
note: zero_sex omitted because of collinearity.
note: zero_exp omitted because of collinearity.
note: zero_biden omitted because of collinearity.
note: zero_dist omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      7,233
                                                F(38, 1446)       =      10.79
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0662
                                                Root MSE          =     .37231

                                      (Std. err. adjusted for 1,447 clusters in r_id)
-------------------------------------------------------------------------------------
                    |               Robust
    out_fair_bwdiff | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |   .0139265   .0076268     1.83   0.068    -.0010342    .0288872
           zero_sex |          0  (omitted)
     cand_exp_teach |  -.0112882   .0112302    -1.01   0.315    -.0333175     .010741
   cand_exp_council |   .0049001   .0112728     0.43   0.664    -.0172127     .027013
    cand_exp_lawyer |   -.010402   .0117992    -0.88   0.378    -.0335474    .0127434
  cand_exp_business |  -.0089442   .0113374    -0.79   0.430    -.0311838    .0132954
           zero_exp |          0  (omitted)
     cand_biden_p59 |   .0079005   .0116374     0.68   0.497    -.0149274    .0307284
     cand_biden_p57 |    .002314   .0112995     0.20   0.838    -.0198512    .0244792
     cand_biden_p55 |    .020527   .0117194     1.75   0.080    -.0024619    .0435159
     cand_biden_p53 |   .0122306   .0114134     1.07   0.284    -.0101581    .0346192
         zero_biden |          0  (omitted)
         cand_dist1 |   .0470683   .0146007     3.22   0.001     .0184276    .0757091
         cand_dist2 |   .0742289   .0150229     4.94   0.000     .0447599     .103698
         cand_dist3 |    .084251   .0159216     5.29   0.000     .0530191    .1154828
         cand_dist4 |   .0287881   .0144329     1.99   0.046     .0004764    .0570997
         cand_dist5 |   .0064837   .0150236     0.43   0.666    -.0229867    .0359542
         cand_dist6 |   .0183777   .0143633     1.28   0.201    -.0097974    .0465528
          zero_dist |          0  (omitted)
 cand_policy_abort1 |    .015618   .0136396     1.15   0.252    -.0111375    .0423735
 cand_policy_abort2 |   .0051392   .0130142     0.39   0.693    -.0203895     .030668
   cand_policy_tax1 |   .0252993   .0134408     1.88   0.060    -.0010662    .0516647
   cand_policy_tax2 |   .0194576   .0132096     1.47   0.141    -.0064544    .0453697
cand_policy_health1 |    .015918   .0133605     1.19   0.234    -.0102901    .0421262
cand_policy_health2 |   .0239248   .0133908     1.79   0.074    -.0023428    .0501923
   cand_policy_eco1 |   .0220292   .0121881     1.81   0.071     -.001879    .0459373
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          white_aa1 |   .0467187   .0229738     2.03   0.042     .0016532    .0917842
          white_aa2 |   .0410289   .0231961     1.77   0.077    -.0044727    .0865304
          white_aa3 |  -.1027482   .0221974    -4.63   0.000    -.1462908   -.0592056
          black_aa0 |   .1868773    .022748     8.22   0.000     .1422546       .2315
          black_aa1 |   .2470242   .0230655    10.71   0.000     .2017789    .2922696
          black_aa2 |   .2276338   .0230118     9.89   0.000     .1824938    .2727738
          black_aa3 |   .1179799   .0222085     5.31   0.000     .0744156    .1615442
          asian_aa0 |   .0384585   .0216096     1.78   0.075     -.003931     .080848
          asian_aa1 |    .095862   .0233697     4.10   0.000     .0500199    .1417041
          asian_aa2 |   .1096244   .0230638     4.75   0.000     .0643822    .1548665
          asian_aa3 |   .0160585   .0221627     0.72   0.469    -.0274159     .059533
          hispa_aa0 |   .0634578   .0200615     3.16   0.002     .0241051    .1028104
          hispa_aa1 |   .1206673   .0236912     5.09   0.000     .0741945    .1671401
          hispa_aa2 |   .1046724   .0233395     4.48   0.000     .0588895    .1504552
          hispa_aa3 |    .004609   .0228092     0.20   0.840    -.0401336    .0493517
           cand_age |  -.0000902   .0007096    -0.13   0.899    -.0014822    .0013017
              _cons |   -.068754   .0444104    -1.55   0.122    -.1558697    .0183617
-------------------------------------------------------------------------------------

 ( 1)  black_aa1 + _cons = 0

------------------------------------------------------------------------------
out_fair_b~f | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |   .1782702    .045512     3.92   0.000     .0889937    .2675467
------------------------------------------------------------------------------

 ( 1)  white_aa1 + _cons = 0

------------------------------------------------------------------------------
out_fair_b~f | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |  -.0220354   .0438331    -0.50   0.615    -.1080186    .0639479
------------------------------------------------------------------------------
note: zero_sex omitted because of collinearity.
note: zero_exp omitted because of collinearity.
note: zero_biden omitted because of collinearity.
note: zero_dist omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      7,233
                                                F(38, 1446)       =      10.79
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0662
                                                Root MSE          =     .37231

                                      (Std. err. adjusted for 1,447 clusters in r_id)
-------------------------------------------------------------------------------------
                    |               Robust
    out_fair_bwdiff | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |   .0139265   .0076268     1.83   0.068    -.0010342    .0288872
           zero_sex |          0  (omitted)
     cand_exp_teach |  -.0112882   .0112302    -1.01   0.315    -.0333175     .010741
   cand_exp_council |   .0049001   .0112728     0.43   0.664    -.0172127     .027013
    cand_exp_lawyer |   -.010402   .0117992    -0.88   0.378    -.0335474    .0127434
  cand_exp_business |  -.0089442   .0113374    -0.79   0.430    -.0311838    .0132954
           zero_exp |          0  (omitted)
     cand_biden_p59 |   .0079005   .0116374     0.68   0.497    -.0149274    .0307284
     cand_biden_p57 |    .002314   .0112995     0.20   0.838    -.0198512    .0244792
     cand_biden_p55 |    .020527   .0117194     1.75   0.080    -.0024619    .0435159
     cand_biden_p53 |   .0122306   .0114134     1.07   0.284    -.0101581    .0346192
         zero_biden |          0  (omitted)
         cand_dist1 |   .0470683   .0146007     3.22   0.001     .0184276    .0757091
         cand_dist2 |   .0742289   .0150229     4.94   0.000     .0447599     .103698
         cand_dist3 |    .084251   .0159216     5.29   0.000     .0530191    .1154828
         cand_dist4 |   .0287881   .0144329     1.99   0.046     .0004764    .0570997
         cand_dist5 |   .0064837   .0150236     0.43   0.666    -.0229867    .0359542
         cand_dist6 |   .0183777   .0143633     1.28   0.201    -.0097974    .0465528
          zero_dist |          0  (omitted)
 cand_policy_abort1 |    .015618   .0136396     1.15   0.252    -.0111375    .0423735
 cand_policy_abort2 |   .0051392   .0130142     0.39   0.693    -.0203895     .030668
   cand_policy_tax1 |   .0252993   .0134408     1.88   0.060    -.0010662    .0516647
   cand_policy_tax2 |   .0194576   .0132096     1.47   0.141    -.0064544    .0453697
cand_policy_health1 |    .015918   .0133605     1.19   0.234    -.0102901    .0421262
cand_policy_health2 |   .0239248   .0133908     1.79   0.074    -.0023428    .0501923
   cand_policy_eco1 |   .0220292   .0121881     1.81   0.071     -.001879    .0459373
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          white_aa1 |   .0467187   .0229738     2.03   0.042     .0016532    .0917842
          white_aa2 |   .0410289   .0231961     1.77   0.077    -.0044727    .0865304
          white_aa3 |  -.1027482   .0221974    -4.63   0.000    -.1462908   -.0592056
          black_aa0 |   .1868773    .022748     8.22   0.000     .1422546       .2315
          black_aa1 |   .2470242   .0230655    10.71   0.000     .2017789    .2922696
          black_aa2 |   .2276338   .0230118     9.89   0.000     .1824938    .2727738
          black_aa3 |   .1179799   .0222085     5.31   0.000     .0744156    .1615442
          asian_aa0 |   .0384585   .0216096     1.78   0.075     -.003931     .080848
          asian_aa1 |    .095862   .0233697     4.10   0.000     .0500199    .1417041
          asian_aa2 |   .1096244   .0230638     4.75   0.000     .0643822    .1548665
          asian_aa3 |   .0160585   .0221627     0.72   0.469    -.0274159     .059533
          hispa_aa0 |   .0634578   .0200615     3.16   0.002     .0241051    .1028104
          hispa_aa1 |   .1206673   .0236912     5.09   0.000     .0741945    .1671401
          hispa_aa2 |   .1046724   .0233395     4.48   0.000     .0588895    .1504552
          hispa_aa3 |    .004609   .0228092     0.20   0.840    -.0401336    .0493517
           cand_age |  -.0000902   .0007096    -0.13   0.899    -.0014822    .0013017
              _cons |   -.068754   .0444104    -1.55   0.122    -.1558697    .0183617
-------------------------------------------------------------------------------------

 ( 1)  black_aa2 + _cons = 0

------------------------------------------------------------------------------
out_fair_b~f | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |   .1588798   .0452204     3.51   0.000     .0701753    .2475843
------------------------------------------------------------------------------

 ( 1)  white_aa2 + _cons = 0

------------------------------------------------------------------------------
out_fair_b~f | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |  -.0277251   .0460213    -0.60   0.547    -.1180007    .0625504
------------------------------------------------------------------------------
note: zero_sex omitted because of collinearity.
note: zero_exp omitted because of collinearity.
note: zero_biden omitted because of collinearity.
note: zero_dist omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      7,233
                                                F(38, 1446)       =      10.79
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0662
                                                Root MSE          =     .37231

                                      (Std. err. adjusted for 1,447 clusters in r_id)
-------------------------------------------------------------------------------------
                    |               Robust
    out_fair_bwdiff | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |   .0139265   .0076268     1.83   0.068    -.0010342    .0288872
           zero_sex |          0  (omitted)
     cand_exp_teach |  -.0112882   .0112302    -1.01   0.315    -.0333175     .010741
   cand_exp_council |   .0049001   .0112728     0.43   0.664    -.0172127     .027013
    cand_exp_lawyer |   -.010402   .0117992    -0.88   0.378    -.0335474    .0127434
  cand_exp_business |  -.0089442   .0113374    -0.79   0.430    -.0311838    .0132954
           zero_exp |          0  (omitted)
     cand_biden_p59 |   .0079005   .0116374     0.68   0.497    -.0149274    .0307284
     cand_biden_p57 |    .002314   .0112995     0.20   0.838    -.0198512    .0244792
     cand_biden_p55 |    .020527   .0117194     1.75   0.080    -.0024619    .0435159
     cand_biden_p53 |   .0122306   .0114134     1.07   0.284    -.0101581    .0346192
         zero_biden |          0  (omitted)
         cand_dist1 |   .0470683   .0146007     3.22   0.001     .0184276    .0757091
         cand_dist2 |   .0742289   .0150229     4.94   0.000     .0447599     .103698
         cand_dist3 |    .084251   .0159216     5.29   0.000     .0530191    .1154828
         cand_dist4 |   .0287881   .0144329     1.99   0.046     .0004764    .0570997
         cand_dist5 |   .0064837   .0150236     0.43   0.666    -.0229867    .0359542
         cand_dist6 |   .0183777   .0143633     1.28   0.201    -.0097974    .0465528
          zero_dist |          0  (omitted)
 cand_policy_abort1 |    .015618   .0136396     1.15   0.252    -.0111375    .0423735
 cand_policy_abort2 |   .0051392   .0130142     0.39   0.693    -.0203895     .030668
   cand_policy_tax1 |   .0252993   .0134408     1.88   0.060    -.0010662    .0516647
   cand_policy_tax2 |   .0194576   .0132096     1.47   0.141    -.0064544    .0453697
cand_policy_health1 |    .015918   .0133605     1.19   0.234    -.0102901    .0421262
cand_policy_health2 |   .0239248   .0133908     1.79   0.074    -.0023428    .0501923
   cand_policy_eco1 |   .0220292   .0121881     1.81   0.071     -.001879    .0459373
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          white_aa1 |   .0467187   .0229738     2.03   0.042     .0016532    .0917842
          white_aa2 |   .0410289   .0231961     1.77   0.077    -.0044727    .0865304
          white_aa3 |  -.1027482   .0221974    -4.63   0.000    -.1462908   -.0592056
          black_aa0 |   .1868773    .022748     8.22   0.000     .1422546       .2315
          black_aa1 |   .2470242   .0230655    10.71   0.000     .2017789    .2922696
          black_aa2 |   .2276338   .0230118     9.89   0.000     .1824938    .2727738
          black_aa3 |   .1179799   .0222085     5.31   0.000     .0744156    .1615442
          asian_aa0 |   .0384585   .0216096     1.78   0.075     -.003931     .080848
          asian_aa1 |    .095862   .0233697     4.10   0.000     .0500199    .1417041
          asian_aa2 |   .1096244   .0230638     4.75   0.000     .0643822    .1548665
          asian_aa3 |   .0160585   .0221627     0.72   0.469    -.0274159     .059533
          hispa_aa0 |   .0634578   .0200615     3.16   0.002     .0241051    .1028104
          hispa_aa1 |   .1206673   .0236912     5.09   0.000     .0741945    .1671401
          hispa_aa2 |   .1046724   .0233395     4.48   0.000     .0588895    .1504552
          hispa_aa3 |    .004609   .0228092     0.20   0.840    -.0401336    .0493517
           cand_age |  -.0000902   .0007096    -0.13   0.899    -.0014822    .0013017
              _cons |   -.068754   .0444104    -1.55   0.122    -.1558697    .0183617
-------------------------------------------------------------------------------------

 ( 1)  black_aa3 + _cons = 0

------------------------------------------------------------------------------
out_fair_b~f | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |   .0492259   .0443503     1.11   0.267    -.0377718    .1362236
------------------------------------------------------------------------------

 ( 1)  white_aa3 + _cons = 0

------------------------------------------------------------------------------
out_fair_b~f | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |  -.1715022   .0442552    -3.88   0.000    -.2583134    -.084691
------------------------------------------------------------------------------

.         postclose `temp2'

.         
.         preserve

.                 use `tempf2', clear

.                 list

     +----------------------------------+
     |       var   favor_c~f   favor_se |
     |----------------------------------|
  1. | black_aa0    .1181233   .0446224 |
  2. | white_aa0    -.068754   .0444104 |
  3. | black_aa1    .1782702   .0455119 |
  4. | white_aa1   -.0220354   .0438331 |
  5. | black_aa2    .1588798   .0452204 |
     |----------------------------------|
  6. | white_aa2   -.0277251   .0460212 |
  7. | black_aa3    .0492259   .0443503 |
  8. | white_aa3   -.1715022   .0442552 |
     +----------------------------------+

.                 
.                 reshape long favor_, i(var) j(stat) s 
(j = coef se)

Data                               Wide   ->   Long
-----------------------------------------------------------------------------
Number of observations                8   ->   16          
Number of variables                   3   ->   3           
j variable (2 values)                     ->   stat
xij variables:
                    favor_coef favor_se   ->   favor_
-----------------------------------------------------------------------------

.                 
.                 merge 1:1 var stat using `tempf'

    Result                      Number of obs
    -----------------------------------------
    Not matched                             0
    Matched                                16  (_merge==3)
    -----------------------------------------

.                 drop _m

.                 
.                 gen favor = "0"+string(round(favor_, 0.002))

.                 replace favor = subinstr(favor, "-","", .)
(4 real changes made)

.                 replace favor = "-"+favor if substr(string(favor_), 1, 1) == "-"
(4 real changes made)

.                 //replace favor = "("+favor+")" if stat == "se"
.                 
.                 gen ideo = "0"+string(round(ideo_, 0.002))

.                 replace ideo = subinstr(ideo, "-","", .)
(0 real changes made)

.                 replace ideo = "-"+ideo if substr(string(ideo_), 1, 1) == "-"
(0 real changes made)

.                 //replace ideo = "("+ideo+")" if stat == "se"
.                 
.                 drop favor_ ideo_

.                 list

     +-----------------------------------+
     |       var   stat    favor    ideo |
     |-----------------------------------|
  1. | black_aa0   coef    0.118    0.68 |
  2. | black_aa0     se    0.044   0.028 |
  3. | black_aa1   coef    0.178   0.716 |
  4. | black_aa1     se    0.046   0.028 |
  5. | black_aa2   coef    0.158     0.7 |
     |-----------------------------------|
  6. | black_aa2     se    0.046   0.028 |
  7. | black_aa3   coef     0.05   0.646 |
  8. | black_aa3     se    0.044    0.03 |
  9. | white_aa0   coef   -0.068   0.686 |
 10. | white_aa0     se    0.044   0.028 |
     |-----------------------------------|
 11. | white_aa1   coef   -0.022     0.7 |
 12. | white_aa1     se    0.044   0.028 |
 13. | white_aa2   coef   -0.028   0.696 |
 14. | white_aa2     se    0.046   0.028 |
 15. | white_aa3   coef   -0.172   0.624 |
     |-----------------------------------|
 16. | white_aa3     se    0.044   0.028 |
     +-----------------------------------+

.                 
.                 gen order = . 
(16 missing values generated)

.                 replace order = 1 if var == "black_aa0"
(2 real changes made)

.                 replace order = 2 if var == "white_aa0"
(2 real changes made)

.                 replace order = 3 if var == "black_aa1"
(2 real changes made)

.                 replace order = 4 if var == "white_aa1"
(2 real changes made)

.                 replace order = 5 if var == "black_aa2"
(2 real changes made)

.                 replace order = 6 if var == "white_aa2"
(2 real changes made)

.                 replace order = 7 if var == "black_aa3"
(2 real changes made)

.                 replace order = 8 if var == "white_aa3"
(2 real changes made)

.                 replace order = order + 0.5 if stat == "se"
(8 real changes made)

.                 sort order

.                 
.                 
.                 gen varname = ""
(16 missing values generated)

.                 replace varname = "Black X No Position" if order == 1
variable varname was str1 now str19
(1 real change made)

.                 replace varname = "White X No Position" if order == 2
(1 real change made)

.                 replace varname = "Black X Expand" if order == 3
(1 real change made)

.                 replace varname = "White X Expand" if order == 4
(1 real change made)

.                 replace varname = "Black X Keep" if order == 5
(1 real change made)

.                 replace varname = "White X Keep" if order == 6
(1 real change made)

.                 replace varname = "Black X End" if order == 7
(1 real change made)

.                 replace varname = "White X End" if order == 8
(1 real change made)

.                 
.                 order var stat varname ideo favor

.                 drop order var

.                 
.                 list

     +---------------------------------------------+
     | stat               varname    ideo    favor |
     |---------------------------------------------|
  1. | coef   Black X No Position    0.68    0.118 |
  2. |   se                         0.028    0.044 |
  3. | coef   White X No Position   0.686   -0.068 |
  4. |   se                         0.028    0.044 |
  5. | coef        Black X Expand   0.716    0.178 |
     |---------------------------------------------|
  6. |   se                         0.028    0.046 |
  7. | coef        White X Expand     0.7   -0.022 |
  8. |   se                         0.028    0.044 |
  9. | coef          Black X Keep     0.7    0.158 |
 10. |   se                         0.028    0.046 |
     |---------------------------------------------|
 11. | coef          White X Keep   0.696   -0.028 |
 12. |   se                         0.028    0.046 |
 13. | coef           Black X End   0.646     0.05 |
 14. |   se                          0.03    0.044 |
 15. | coef           White X End   0.624   -0.172 |
     |---------------------------------------------|
 16. |   se                         0.028    0.044 |
     +---------------------------------------------+

.                 
.                 outsheet using table_4.csv, comma replace
(file table_4.csv not found)

.         restore

.         
. // Table 5 (Study 2)
.         // Ideology
.         rename out_fair_bwdiff out_favor

.         foreach var in ideo favor {
  2.                 tempname temp_`var'
  3.                 tempfile tempf_`var'
  4.                 
.                 postfile `temp_`var'' str20 var `var'_coef `var'_se using `tempf_`var''
  5.                 
.                 reg out_`var' `reg_sex' `reg_exp' `reg_biden' `reg_distpop' `reg_issues' `int' ///
>                         cand_age, vce(cluster r_id)
  6.                 
.                         lincom black_aa0 - white_aa0
  7.                         post `temp_`var'' ("BW_NoPosition") (r(estimate)) (r(se))
  8.                         
.                         lincom black_aa3 - white_aa0
  9.                         post `temp_`var'' ("BCons_WNoPos") (r(estimate)) (r(se))
 10.                                 
.                         lincom black_aa3 - white_aa3
 11.                         post `temp_`var'' ("BW_Cons") (r(estimate)) (r(se))
 12.                         
.                         lincom black_aa1 - white_aa1
 13.                         post `temp_`var'' ("BW_Lib") (r(estimate)) (r(se))
 14.                         
.                 postclose `temp_`var''
 15.         }
note: zero_sex omitted because of collinearity.
note: zero_exp omitted because of collinearity.
note: zero_biden omitted because of collinearity.
note: zero_dist omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      7,230
                                                F(38, 1446)       =       7.00
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0371
                                                Root MSE          =     .23868

                                      (Std. err. adjusted for 1,447 clusters in r_id)
-------------------------------------------------------------------------------------
                    |               Robust
           out_ideo | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |   .0059291   .0046498     1.28   0.202     -.003192    .0150501
           zero_sex |          0  (omitted)
     cand_exp_teach |   .0122159   .0065721     1.86   0.063    -.0006761    .0251078
   cand_exp_council |   .0051068   .0064179     0.80   0.426    -.0074826    .0176962
    cand_exp_lawyer |   .0030542   .0066661     0.46   0.647    -.0100221    .0161305
  cand_exp_business |   .0055399   .0065377     0.85   0.397    -.0072845    .0183642
           zero_exp |          0  (omitted)
     cand_biden_p59 |   .0000409   .0066104     0.01   0.995    -.0129261    .0130079
     cand_biden_p57 |   .0103569   .0066061     1.57   0.117    -.0026016    .0233154
     cand_biden_p55 |   .0030348   .0064071     0.47   0.636    -.0095334     .015603
     cand_biden_p53 |   .0030762   .0063017     0.49   0.626    -.0092852    .0154376
         zero_biden |          0  (omitted)
         cand_dist1 |  -.0113719   .0085274    -1.33   0.183    -.0280992    .0053555
         cand_dist2 |  -.0093389   .0083509    -1.12   0.264    -.0257201    .0070422
         cand_dist3 |  -.0159317   .0086303    -1.85   0.065     -.032861    .0009976
         cand_dist4 |  -.0078922   .0086635    -0.91   0.362    -.0248866    .0091022
         cand_dist5 |  -.0150726   .0089194    -1.69   0.091    -.0325689    .0024237
         cand_dist6 |  -.0179895   .0085356    -2.11   0.035    -.0347331   -.0012459
          zero_dist |          0  (omitted)
 cand_policy_abort1 |   .0865966   .0093206     9.29   0.000     .0683133    .1048799
 cand_policy_abort2 |   .0222603   .0085781     2.60   0.010     .0054334    .0390871
   cand_policy_tax1 |   .0099431   .0091723     1.08   0.279    -.0080493    .0279355
   cand_policy_tax2 |  -.0153925    .008837    -1.74   0.082    -.0327271    .0019421
cand_policy_health1 |   .0336736   .0088891     3.79   0.000     .0162367    .0511104
cand_policy_health2 |   .0063585   .0087873     0.72   0.469    -.0108788    .0235958
   cand_policy_eco1 |   .0132894   .0076099     1.75   0.081    -.0016382    .0282169
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          white_aa1 |   .0139106   .0144716     0.96   0.337     -.014477    .0422983
          white_aa2 |   .0115353   .0148021     0.78   0.436    -.0175006    .0405711
          white_aa3 |  -.0613646   .0146132    -4.20   0.000      -.09003   -.0326992
          black_aa0 |   -.005849   .0135541    -0.43   0.666    -.0324368    .0207389
          black_aa1 |   .0312423   .0134733     2.32   0.021     .0048129    .0576716
          black_aa2 |   .0155517    .014348     1.08   0.279    -.0125934    .0436968
          black_aa3 |   -.039669    .013763    -2.88   0.004    -.0666666   -.0126714
          asian_aa0 |   -.019575   .0149818    -1.31   0.192    -.0489633    .0098133
          asian_aa1 |   .0104106   .0151699     0.69   0.493    -.0193468    .0401679
          asian_aa2 |    .022626   .0151685     1.49   0.136    -.0071287    .0523807
          asian_aa3 |  -.0413389   .0147379    -2.80   0.005     -.070249   -.0124289
          hispa_aa0 |   .0032418   .0142965     0.23   0.821    -.0248022    .0312859
          hispa_aa1 |   .0261759   .0154693     1.69   0.091    -.0041688    .0565206
          hispa_aa2 |   .0247045    .014716     1.68   0.093    -.0041625    .0535714
          hispa_aa3 |  -.0491622   .0158941    -3.09   0.002    -.0803401   -.0179842
           cand_age |  -.0007007   .0004648    -1.51   0.132    -.0016124     .000211
              _cons |   .6851087    .028839    23.76   0.000     .6285379    .7416796
-------------------------------------------------------------------------------------

 ( 1)  - o.white_aa0 + black_aa0 = 0

------------------------------------------------------------------------------
    out_ideo | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |   -.005849   .0135541    -0.43   0.666    -.0324368    .0207389
------------------------------------------------------------------------------

 ( 1)  - o.white_aa0 + black_aa3 = 0

------------------------------------------------------------------------------
    out_ideo | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |   -.039669    .013763    -2.88   0.004    -.0666666   -.0126714
------------------------------------------------------------------------------

 ( 1)  - white_aa3 + black_aa3 = 0

------------------------------------------------------------------------------
    out_ideo | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |   .0216955   .0142603     1.52   0.128    -.0062775    .0496686
------------------------------------------------------------------------------

 ( 1)  - white_aa1 + black_aa1 = 0

------------------------------------------------------------------------------
    out_ideo | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |   .0173316   .0134101     1.29   0.196    -.0089736    .0436369
------------------------------------------------------------------------------
note: zero_sex omitted because of collinearity.
note: zero_exp omitted because of collinearity.
note: zero_biden omitted because of collinearity.
note: zero_dist omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      7,233
                                                F(38, 1446)       =      10.79
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0662
                                                Root MSE          =     .37231

                                      (Std. err. adjusted for 1,447 clusters in r_id)
-------------------------------------------------------------------------------------
                    |               Robust
          out_favor | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |   .0139265   .0076268     1.83   0.068    -.0010342    .0288872
           zero_sex |          0  (omitted)
     cand_exp_teach |  -.0112882   .0112302    -1.01   0.315    -.0333175     .010741
   cand_exp_council |   .0049001   .0112728     0.43   0.664    -.0172127     .027013
    cand_exp_lawyer |   -.010402   .0117992    -0.88   0.378    -.0335474    .0127434
  cand_exp_business |  -.0089442   .0113374    -0.79   0.430    -.0311838    .0132954
           zero_exp |          0  (omitted)
     cand_biden_p59 |   .0079005   .0116374     0.68   0.497    -.0149274    .0307284
     cand_biden_p57 |    .002314   .0112995     0.20   0.838    -.0198512    .0244792
     cand_biden_p55 |    .020527   .0117194     1.75   0.080    -.0024619    .0435159
     cand_biden_p53 |   .0122306   .0114134     1.07   0.284    -.0101581    .0346192
         zero_biden |          0  (omitted)
         cand_dist1 |   .0470683   .0146007     3.22   0.001     .0184276    .0757091
         cand_dist2 |   .0742289   .0150229     4.94   0.000     .0447599     .103698
         cand_dist3 |    .084251   .0159216     5.29   0.000     .0530191    .1154828
         cand_dist4 |   .0287881   .0144329     1.99   0.046     .0004764    .0570997
         cand_dist5 |   .0064837   .0150236     0.43   0.666    -.0229867    .0359542
         cand_dist6 |   .0183777   .0143633     1.28   0.201    -.0097974    .0465528
          zero_dist |          0  (omitted)
 cand_policy_abort1 |    .015618   .0136396     1.15   0.252    -.0111375    .0423735
 cand_policy_abort2 |   .0051392   .0130142     0.39   0.693    -.0203895     .030668
   cand_policy_tax1 |   .0252993   .0134408     1.88   0.060    -.0010662    .0516647
   cand_policy_tax2 |   .0194576   .0132096     1.47   0.141    -.0064544    .0453697
cand_policy_health1 |    .015918   .0133605     1.19   0.234    -.0102901    .0421262
cand_policy_health2 |   .0239248   .0133908     1.79   0.074    -.0023428    .0501923
   cand_policy_eco1 |   .0220292   .0121881     1.81   0.071     -.001879    .0459373
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          white_aa1 |   .0467187   .0229738     2.03   0.042     .0016532    .0917842
          white_aa2 |   .0410289   .0231961     1.77   0.077    -.0044727    .0865304
          white_aa3 |  -.1027482   .0221974    -4.63   0.000    -.1462908   -.0592056
          black_aa0 |   .1868773    .022748     8.22   0.000     .1422546       .2315
          black_aa1 |   .2470242   .0230655    10.71   0.000     .2017789    .2922696
          black_aa2 |   .2276338   .0230118     9.89   0.000     .1824938    .2727738
          black_aa3 |   .1179799   .0222085     5.31   0.000     .0744156    .1615442
          asian_aa0 |   .0384585   .0216096     1.78   0.075     -.003931     .080848
          asian_aa1 |    .095862   .0233697     4.10   0.000     .0500199    .1417041
          asian_aa2 |   .1096244   .0230638     4.75   0.000     .0643822    .1548665
          asian_aa3 |   .0160585   .0221627     0.72   0.469    -.0274159     .059533
          hispa_aa0 |   .0634578   .0200615     3.16   0.002     .0241051    .1028104
          hispa_aa1 |   .1206673   .0236912     5.09   0.000     .0741945    .1671401
          hispa_aa2 |   .1046724   .0233395     4.48   0.000     .0588895    .1504552
          hispa_aa3 |    .004609   .0228092     0.20   0.840    -.0401336    .0493517
           cand_age |  -.0000902   .0007096    -0.13   0.899    -.0014822    .0013017
              _cons |   -.068754   .0444104    -1.55   0.122    -.1558697    .0183617
-------------------------------------------------------------------------------------

 ( 1)  - o.white_aa0 + black_aa0 = 0

------------------------------------------------------------------------------
   out_favor | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |   .1868773    .022748     8.22   0.000     .1422546       .2315
------------------------------------------------------------------------------

 ( 1)  - o.white_aa0 + black_aa3 = 0

------------------------------------------------------------------------------
   out_favor | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |   .1179799   .0222085     5.31   0.000     .0744156    .1615442
------------------------------------------------------------------------------

 ( 1)  - white_aa3 + black_aa3 = 0

------------------------------------------------------------------------------
   out_favor | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |   .2207281   .0236267     9.34   0.000     .1743818    .2670744
------------------------------------------------------------------------------

 ( 1)  - white_aa1 + black_aa1 = 0

------------------------------------------------------------------------------
   out_favor | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |   .2003056   .0230934     8.67   0.000     .1550054    .2456057
------------------------------------------------------------------------------

.                 
.         use `tempf_ideo', clear

.         reshape long ideo_, i(var) j(stat) s 
(j = coef se)

Data                               Wide   ->   Long
-----------------------------------------------------------------------------
Number of observations                4   ->   8           
Number of variables                   3   ->   3           
j variable (2 values)                     ->   stat
xij variables:
                      ideo_coef ideo_se   ->   ideo_
-----------------------------------------------------------------------------

.         list

     +---------------------------------+
     |           var   stat      ideo_ |
     |---------------------------------|
  1. |  BCons_WNoPos   coef   -.039669 |
  2. |  BCons_WNoPos     se    .013763 |
  3. |       BW_Cons   coef   .0216955 |
  4. |       BW_Cons     se   .0142603 |
  5. |        BW_Lib   coef   .0173316 |
     |---------------------------------|
  6. |        BW_Lib     se   .0134101 |
  7. | BW_NoPosition   coef   -.005849 |
  8. | BW_NoPosition     se   .0135541 |
     +---------------------------------+

.         save `tempf_ideo', replace
file C:\Users\wujen\AppData\Local\Temp\ST_310c_00000b.tmp saved as .dta format

.         
.         
.         use `tempf_favor', clear

.         reshape long favor_, i(var) j(stat) s
(j = coef se)

Data                               Wide   ->   Long
-----------------------------------------------------------------------------
Number of observations                4   ->   8           
Number of variables                   3   ->   3           
j variable (2 values)                     ->   stat
xij variables:
                    favor_coef favor_se   ->   favor_
-----------------------------------------------------------------------------

.         list

     +---------------------------------+
     |           var   stat     favor_ |
     |---------------------------------|
  1. |  BCons_WNoPos   coef   .1179799 |
  2. |  BCons_WNoPos     se   .0222085 |
  3. |       BW_Cons   coef   .2207281 |
  4. |       BW_Cons     se   .0236267 |
  5. |        BW_Lib   coef   .2003056 |
     |---------------------------------|
  6. |        BW_Lib     se   .0230934 |
  7. | BW_NoPosition   coef   .1868773 |
  8. | BW_NoPosition     se    .022748 |
     +---------------------------------+

.         merge 1:1 var stat using `tempf_ideo'

    Result                      Number of obs
    -----------------------------------------
    Not matched                             0
    Matched                                 8  (_merge==3)
    -----------------------------------------

.         drop _m

.         list

     +--------------------------------------------+
     |           var   stat     favor_      ideo_ |
     |--------------------------------------------|
  1. |  BCons_WNoPos   coef   .1179799   -.039669 |
  2. |  BCons_WNoPos     se   .0222085    .013763 |
  3. |       BW_Cons   coef   .2207281   .0216955 |
  4. |       BW_Cons     se   .0236267   .0142603 |
  5. |        BW_Lib   coef   .2003056   .0173316 |
     |--------------------------------------------|
  6. |        BW_Lib     se   .0230934   .0134101 |
  7. | BW_NoPosition   coef   .1868773   -.005849 |
  8. | BW_NoPosition     se    .022748   .0135541 |
     +--------------------------------------------+

.         
.         gen favor = "0"+string(round(favor_, 0.002))

.         replace favor = subinstr(favor, "-","", .)
(0 real changes made)

.         replace favor = "-"+favor if substr(string(favor_), 1, 1) == "-"
(0 real changes made)

.         
.         gen ideo = "0"+string(round(ideo_, 0.002))

.         replace ideo = subinstr(ideo, "-","", .)
(2 real changes made)

.         replace ideo = "-"+ideo if substr(string(ideo_), 1, 1) == "-"
(2 real changes made)

.         
.         drop favor_ ideo_

.         list

     +---------------------------------------+
     |           var   stat   favor     ideo |
     |---------------------------------------|
  1. |  BCons_WNoPos   coef   0.118    -0.04 |
  2. |  BCons_WNoPos     se   0.022    0.014 |
  3. |       BW_Cons   coef    0.22    0.022 |
  4. |       BW_Cons     se   0.024    0.014 |
  5. |        BW_Lib   coef     0.2    0.018 |
     |---------------------------------------|
  6. |        BW_Lib     se   0.024    0.014 |
  7. | BW_NoPosition   coef   0.186   -0.006 |
  8. | BW_NoPosition     se   0.022    0.014 |
     +---------------------------------------+

.         
.         gen order = . 
(8 missing values generated)

.         replace order = 1 if var == "BW_NoPosition"
(2 real changes made)

.         replace order = 2 if var == "BCons_WNoPos"
(2 real changes made)

.         replace order = 3 if var == "BW_Cons"
(2 real changes made)

.         replace order = 4 if var == "BW_Lib"
(2 real changes made)

.         replace order = order + 0.5 if stat == "se"
(4 real changes made)

.         sort order

.         
.         
.         gen varname = ""
(8 missing values generated)

.         replace varname = "Black-White, No Position" if order == 1
variable varname was str1 now str24
(1 real change made)

.         replace varname = "Black, Conserative - White, No Position" if order == 2
variable varname was str24 now str39
(1 real change made)

.         replace varname = "Black-White, Conservative" if order == 3
(1 real change made)

.         replace varname = "Black, Liberal - White, Liberal" if order == 4
(1 real change made)

. 
.         
.         order var stat varname ideo favor

.         drop order var

.         
.         list

     +-----------------------------------------------------------------+
     | stat                                   varname     ideo   favor |
     |-----------------------------------------------------------------|
  1. | coef                  Black-White, No Position   -0.006   0.186 |
  2. |   se                                              0.014   0.022 |
  3. | coef   Black, Conserative - White, No Position    -0.04   0.118 |
  4. |   se                                              0.014   0.022 |
  5. | coef                 Black-White, Conservative    0.022    0.22 |
     |-----------------------------------------------------------------|
  6. |   se                                              0.014   0.024 |
  7. | coef           Black, Liberal - White, Liberal    0.018     0.2 |
  8. |   se                                              0.014   0.024 |
     +-----------------------------------------------------------------+

.         
.         outsheet using table_5.csv, comma replace 
(file table_5.csv not found)

.         
. 
end of do-file

. 
. // Files 5-10 are appendix tables/figures
. do 5_appendix_a1.do

. /*
>         Appendix A Figure A1
>         
>         Main figure broken out by prejudice measures. 
> 
> */
. 
. 
. use data_study_1.dta, clear

. 
. // Set omitted categories
.         gen zero_race = 0

.         label var zero_race "White"

.         gen zero_sex = 0

.         label var zero_sex "Male"

.         gen zero_eco = 0

.         label var zero_eco "Maintain investment in energy"

.         gen zero_aa = 0

.         label var zero_aa "Not shown policy"

.         
. // Set regression variables
.         loc reg_race "cand_black zero_race"

.         loc reg_sex "cand_female zero_sex"

.         loc reg_issues "cand_policy_abort1 cand_policy_abort2 cand_policy_tax1 cand_policy_tax2"

.         loc reg_issues "`reg_issues' cand_policy_health1 cand_policy_health2 cand_policy_eco1 zero_eco"

.         loc reg_issues_aa "cand_policy_aa1 cand_policy_aa2 cand_policy_aa3 zero_aa"

.                 
. // Interactive Terms for Black Candidate X Affirmative Action
.         gen noracepolicy = cand_policy_aa1 == 0 & cand_policy_aa2 == 0 & cand_policy_aa3 == 0   

.         label var noracepolicy "Not shown position"

.         gen black_aa1 = cand_policy_aa1*cand_black

.         gen black_aa2 = cand_policy_aa2*cand_black

.         gen black_aa3 = cand_policy_aa3*cand_black

.         gen white_aa1 = cand_policy_aa1*cand_white

.         gen white_aa2 = cand_policy_aa2*cand_white

.         gen white_aa3 = cand_policy_aa3*cand_white

.         gen black_aa0 = noracepolicy*cand_black

.         gen white_aa0 = noracepolicy*cand_white

.         label var black_aa0 "Black X No Position"

.         label var white_aa0 "White X No Position"

.         label var black_aa1 "Black X Expand (race)"

.         label var black_aa2 "Black X Keep as is"

.         label var black_aa3 "Black X Replace (class)"

.         label var white_aa1 "White X Expand (race)"

.         label var white_aa2 "White X Keep as is"

.         label var white_aa3 "White X Replace (class)"

.         replace white_aa0 = 0
(294 real changes made)

.         label var noracepolicy "Not shown position"

.         loc int "white_aa0 black_aa0 white_aa1 white_aa2 white_aa3 black_aa1 black_aa2 black_aa3"

.         
. 
. //============================================= Figure A2. Prejudice
.         gen out_fair_bwdiff = out_fair_black - out_fair_white
(226 missing values generated)

.         
.         
.         foreach spec in rr ep { 
  2.                 if "`spec'" == "rr" {
  3.                         loc gr1 "High Racial Resentment"
  4.                         loc gr2 "Low Racial Resentment"
  5.                         loc tit "Racial Resentment Measure"
  6.                         rename resent_binary rr_binary
  7.                 }
  8.         
.                 if "`spec'" == "ep" {
  9.                         loc gr1 "High Explicit Prejudice"
 10.                         loc gr2 "Low Explicit Prejudice"
 11.                         loc tit "Explicit Prejudice Measure"
 12.                         rename overt_binary ep_binary
 13.                 }
 14.                 
.                 reg out_ideo_7 `reg_sex' `reg_issues' `int' cand_age if `spec'_binary == 1, robust
 15.                 eststo ideo_`spec'
 16.                 reg out_ideo_7 `reg_sex' `reg_issues' `int' cand_age if `spec'_binary == 0, robust
 17.                 eststo ideo_n`spec'
 18.                 
.                 reg out_priority_sj `reg_sex' `reg_issues' `int' if `spec'_binary == 1, robust
 19.                 eststo `spec'_out_priority_sj
 20.                 reg out_priority_sj `reg_sex' `reg_issues' `int' if `spec'_binary == 0, robust
 21.                 eststo `spec'n_out_priority_sj
 22.                 
.                 reg out_fair_bwdiff `reg_sex' `reg_issues' `int' if `spec'_binary == 1, robust
 23.                 eststo `spec'_fair
 24.                 reg out_fair_bwdiff `reg_sex' `reg_issues' `int' if `spec'_binary == 0, robust
 25.                 eststo `spec'n_fair
 26. 
.                 coefplot (ideo_`spec', label(`gr2') mc(maroon) ciopts(color(maroon) lw(med))) ///
>                                  (ideo_n`spec', label(`gr2') mc(gs4) ciopts(color(gs4) lw(med))) ///
>                                  , bylabel("{bf:(a) Ideological Liberalness}") || ///
>                                 (`spec'_out_priority_sj, label(`gr1') mc(maroon) ciopts(color(maroon) lw
> (med))) ///
>                                 (`spec'n_out_priority_sj, label(`gr2') mc(gs4) ciopts(color(gs4) lw(med)
> )) ///
>                                 , bylabel("{bf:(b) Prioritize Social Justice}") || ///
>                                 (`spec'_fair, label(`gr1') mc(maroon) ciopts(color(maroon) lw(med))) ///
>                                 (`spec'n_fair, label(`gr2') mc(gs4) ciopts(color(gs4) lw(med))) ///
>                                 , bylabel("{bf:(c) Favor Black over White Constituents}") ///
>                         || , drop(_cons `reg_sex' `reg_issues' cand_age) omitted baselevels ms(c) msize(
> med) ///
>                         xline(0, lc(black)) ylabel(,labsize(small))  ///
>                         subtitle(, bcolor(white) color(black) size(vsmall)) ///
>                         byopts(row(1) ///
>                                 t1title("{bf: `tit'}", size(small))) ///
>                         xtitle("Marginal Effects (Scale 0 to 1)", size(vsmall)) xlabel(-0.2(0.1)0.2,labs
> ize(small)) norecycle ///
>                         legend(order(2 "`gr1'" 4 "`gr2'") size(vsmall)) ///
>                         headings(white_aa0 = "{bf: No Affirmative Action}" ///
>                                 white_aa1 = "{bf: White X Affirmative Action}" ///
>                                 black_aa1 = "{bf: Black X Affirmative Action}", labsize(small)) ///
>                                 saving(fig_`spec'.gph, replace)
 27.                         
.         }
note: zero_sex omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      1,218
                                                F(16, 1201)       =       2.86
                                                Prob > F          =     0.0001
                                                R-squared         =     0.0322
                                                Root MSE          =     .25247

-------------------------------------------------------------------------------------
                    |               Robust
         out_ideo_7 | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |   .0143233   .0145507     0.98   0.325    -.0142243     .042871
           zero_sex |          0  (omitted)
 cand_policy_abort1 |   .1006742   .0238562     4.22   0.000     .0538698    .1474787
 cand_policy_abort2 |   .0563914   .0229026     2.46   0.014     .0114578    .1013249
   cand_policy_tax1 |   .0297125   .0226569     1.31   0.190    -.0147389    .0741639
   cand_policy_tax2 |   .0084064   .0227641     0.37   0.712    -.0362553    .0530682
cand_policy_health1 |   .0442765   .0215536     2.05   0.040     .0019896    .0865634
cand_policy_health2 |    .053691   .0232645     2.31   0.021     .0080475    .0993345
   cand_policy_eco1 |    .027077   .0201629     1.34   0.180    -.0124813    .0666354
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          black_aa0 |   .0515404   .0296155     1.74   0.082    -.0065636    .1096443
          white_aa1 |   .0217666   .0315453     0.69   0.490    -.0401234    .0836567
          white_aa2 |   .0251912   .0325573     0.77   0.439    -.0386843    .0890667
          white_aa3 |     .03085   .0286222     1.08   0.281    -.0253051     .087005
          black_aa1 |    .113756   .0281502     4.04   0.000     .0585271     .168985
          black_aa2 |   .0535024   .0298583     1.79   0.073    -.0050778    .1120827
          black_aa3 |    .043369   .0301623     1.44   0.151    -.0158076    .1025456
           cand_age |   .0000271   .0011941     0.02   0.982    -.0023157      .00237
              _cons |   .5658801   .0693463     8.16   0.000     .4298268    .7019334
-------------------------------------------------------------------------------------
note: zero_sex omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      1,000
                                                F(16, 983)        =       1.22
                                                Prob > F          =     0.2480
                                                R-squared         =     0.0206
                                                Root MSE          =     .26749

-------------------------------------------------------------------------------------
                    |               Robust
         out_ideo_7 | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |  -.0091103   .0170756    -0.53   0.594    -.0426191    .0243984
           zero_sex |          0  (omitted)
 cand_policy_abort1 |   .0589201   .0274156     2.15   0.032     .0051203    .1127199
 cand_policy_abort2 |   .0171334   .0264773     0.65   0.518    -.0348251     .069092
   cand_policy_tax1 |   .0355605    .024521     1.45   0.147     -.012559      .08368
   cand_policy_tax2 |  -.0153663    .025377    -0.61   0.545    -.0651657    .0344331
cand_policy_health1 |   .0361662   .0269702     1.34   0.180    -.0167596    .0890921
cand_policy_health2 |   .0213139   .0262001     0.81   0.416    -.0301007    .0727284
   cand_policy_eco1 |   .0034784   .0242195     0.14   0.886    -.0440495    .0510063
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          black_aa0 |    .033804   .0335482     1.01   0.314    -.0320303    .0996384
          white_aa1 |   .0137376   .0337956     0.41   0.684    -.0525823    .0800574
          white_aa2 |    .039275   .0340717     1.15   0.249    -.0275865    .1061366
          white_aa3 |  -.0217356   .0338435    -0.64   0.521    -.0881494    .0446782
          black_aa1 |   .0418711   .0323179     1.30   0.195     -.021549    .1052912
          black_aa2 |   .0010671   .0382842     0.03   0.978     -.074061    .0761952
          black_aa3 |   .0078569   .0341813     0.23   0.818    -.0592199    .0749336
           cand_age |  -.0022234   .0014093    -1.58   0.115    -.0049891    .0005422
              _cons |   .7373475   .0840252     8.78   0.000     .5724581    .9022369
-------------------------------------------------------------------------------------
note: zero_sex omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      1,131
                                                F(15, 1115)       =       2.68
                                                Prob > F          =     0.0005
                                                R-squared         =     0.0323
                                                Root MSE          =     .35429

-------------------------------------------------------------------------------------
                    |               Robust
    out_priority_sj | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |   -.020991    .021213    -0.99   0.323     -.062613    .0206309
           zero_sex |          0  (omitted)
 cand_policy_abort1 |  -.0253089   .0336499    -0.75   0.452     -.091333    .0407153
 cand_policy_abort2 |  -.0157767   .0334445    -0.47   0.637    -.0813979    .0498446
   cand_policy_tax1 |   .0369009   .0332352     1.11   0.267    -.0283098    .1021115
   cand_policy_tax2 |   .0289846   .0333818     0.87   0.385    -.0365136    .0944829
cand_policy_health1 |   .0233382   .0318007     0.73   0.463    -.0390577    .0857341
cand_policy_health2 |   .0132906   .0354926     0.37   0.708    -.0563492    .0829304
   cand_policy_eco1 |   .0153894   .0304629     0.51   0.614    -.0443817    .0751604
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          black_aa0 |   .0051361   .0426878     0.12   0.904    -.0786214    .0888935
          white_aa1 |    .095185   .0442488     2.15   0.032     .0083648    .1820052
          white_aa2 |   .0685397   .0454881     1.51   0.132    -.0207121    .1577916
          white_aa3 |   .0267704    .041931     0.64   0.523    -.0555021    .1090428
          black_aa1 |   .1714326   .0434155     3.95   0.000     .0862474    .2566178
          black_aa2 |   .1086538   .0425196     2.56   0.011     .0252264    .1920812
          black_aa3 |   .1331625   .0416753     3.20   0.001     .0513917    .2149333
              _cons |   .5475025   .0551936     9.92   0.000     .4392074    .6557975
-------------------------------------------------------------------------------------
note: zero_sex omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =        996
                                                F(15, 980)        =       1.30
                                                Prob > F          =     0.1971
                                                R-squared         =     0.0180
                                                Root MSE          =      .3478

-------------------------------------------------------------------------------------
                    |               Robust
    out_priority_sj | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |  -.0168256   .0221369    -0.76   0.447    -.0602668    .0266157
           zero_sex |          0  (omitted)
 cand_policy_abort1 |   .0094136   .0343334     0.27   0.784    -.0579618     .076789
 cand_policy_abort2 |   .0405197   .0351516     1.15   0.249    -.0284614    .1095009
   cand_policy_tax1 |  -.0022625   .0355336    -0.06   0.949    -.0719931    .0674682
   cand_policy_tax2 |  -.0116816   .0337352    -0.35   0.729    -.0778831      .05452
cand_policy_health1 |  -.0134799   .0345529    -0.39   0.697    -.0812862    .0543263
cand_policy_health2 |   .0141292   .0344789     0.41   0.682    -.0535317    .0817901
   cand_policy_eco1 |   .0486062   .0308088     1.58   0.115    -.0118525     .109065
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          black_aa0 |   .0541783   .0439082     1.23   0.218    -.0319866    .1403432
          white_aa1 |   .0043451   .0438845     0.10   0.921    -.0817734    .0904636
          white_aa2 |   .0591176   .0439904     1.34   0.179    -.0272086    .1454438
          white_aa3 |   .0352646   .0418445     0.84   0.400    -.0468505    .1173797
          black_aa1 |   .1230204   .0410463     3.00   0.003     .0424716    .2035692
          black_aa2 |   .0748616   .0450336     1.66   0.097    -.0135118     .163235
          black_aa3 |   .0743756   .0429539     1.73   0.084    -.0099166    .1586678
              _cons |   .6080741   .0556295    10.93   0.000     .4989076    .7172407
-------------------------------------------------------------------------------------
note: zero_sex omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      1,135
                                                F(15, 1119)       =       2.85
                                                Prob > F          =     0.0002
                                                R-squared         =     0.0380
                                                Root MSE          =     .40472

-------------------------------------------------------------------------------------
                    |               Robust
    out_fair_bwdiff | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |   .0285216   .0241484     1.18   0.238    -.0188597    .0759029
           zero_sex |          0  (omitted)
 cand_policy_abort1 |   .0147746   .0394314     0.37   0.708    -.0625932    .0921424
 cand_policy_abort2 |  -.0289463   .0373941    -0.77   0.439    -.1023168    .0444243
   cand_policy_tax1 |   .0353704   .0381474     0.93   0.354    -.0394781     .110219
   cand_policy_tax2 |     .05249   .0352507     1.49   0.137    -.0166749    .1216549
cand_policy_health1 |  -.0165451   .0355937    -0.46   0.642    -.0863829    .0532927
cand_policy_health2 |    .031664   .0424037     0.75   0.455    -.0515358    .1148638
   cand_policy_eco1 |   .0454596   .0345912     1.31   0.189    -.0224114    .1133305
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          black_aa0 |   .1175096   .0435028     2.70   0.007     .0321533    .2028659
          white_aa1 |   .1219127     .04975     2.45   0.014     .0242989    .2195264
          white_aa2 |   .0611256   .0470982     1.30   0.195    -.0312851    .1535362
          white_aa3 |  -.0156763   .0444832    -0.35   0.725    -.1029562    .0716036
          black_aa1 |   .1963301   .0494755     3.97   0.000     .0992548    .2934054
          black_aa2 |   .1743501   .0463453     3.76   0.000     .0834167    .2652835
          black_aa3 |   .1376881   .0461875     2.98   0.003     .0470642     .228312
              _cons |  -.0089686   .0595736    -0.15   0.880    -.1258573      .10792
-------------------------------------------------------------------------------------
note: zero_sex omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =        998
                                                F(15, 982)        =       2.51
                                                Prob > F          =     0.0012
                                                R-squared         =     0.0381
                                                Root MSE          =     .34377

-------------------------------------------------------------------------------------
                    |               Robust
    out_fair_bwdiff | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |   .0430997   .0219925     1.96   0.050     -.000058    .0862574
           zero_sex |          0  (omitted)
 cand_policy_abort1 |   .0209352   .0338882     0.62   0.537    -.0455664    .0874368
 cand_policy_abort2 |   .0415777   .0334695     1.24   0.214    -.0241023    .1072577
   cand_policy_tax1 |   .0017148   .0331996     0.05   0.959    -.0634355    .0668651
   cand_policy_tax2 |   .0242816   .0328871     0.74   0.460    -.0402555    .0888187
cand_policy_health1 |   .0652216   .0327039     1.99   0.046     .0010441    .1293992
cand_policy_health2 |   .0299009   .0363396     0.82   0.411    -.0414113    .1012132
   cand_policy_eco1 |   .0156132   .0306556     0.51   0.611    -.0445448    .0757712
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          black_aa0 |    .072767   .0424418     1.71   0.087    -.0105201     .156054
          white_aa1 |   .0703178   .0432463     1.63   0.104    -.0145479    .1551836
          white_aa2 |   .0944312   .0478425     1.97   0.049      .000546    .1883164
          white_aa3 |  -.0337654   .0435969    -0.77   0.439    -.1193192    .0517884
          black_aa1 |   .1603625   .0419367     3.82   0.000     .0780666    .2426584
          black_aa2 |   .1198151   .0488374     2.45   0.014     .0239774    .2156529
          black_aa3 |   .0939765   .0427307     2.20   0.028     .0101225    .1778304
              _cons |  -.1206763   .0548334    -2.20   0.028    -.2282804   -.0130721
-------------------------------------------------------------------------------------
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(file fig_rr.gph not found)
file fig_rr.gph saved
note: zero_sex omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      1,193
                                                F(16, 1176)       =       2.41
                                                Prob > F          =     0.0015
                                                R-squared         =     0.0284
                                                Root MSE          =     .25476

-------------------------------------------------------------------------------------
                    |               Robust
         out_ideo_7 | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |    .000657    .014983     0.04   0.965    -.0287395    .0300535
           zero_sex |          0  (omitted)
 cand_policy_abort1 |    .080172   .0245287     3.27   0.001     .0320472    .1282968
 cand_policy_abort2 |   .0403394   .0240473     1.68   0.094     -.006841    .0875197
   cand_policy_tax1 |   .0522842   .0232614     2.25   0.025     .0066456    .0979227
   cand_policy_tax2 |   .0092785   .0223763     0.41   0.678    -.0346235    .0531805
cand_policy_health1 |   .0524853    .022422     2.34   0.019     .0084938    .0964769
cand_policy_health2 |   .0217302   .0240922     0.90   0.367    -.0255384    .0689987
   cand_policy_eco1 |    .016223   .0209685     0.77   0.439    -.0249169    .0573629
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          black_aa0 |   .0430686   .0289015     1.49   0.136    -.0136356    .0997729
          white_aa1 |    .026763   .0318698     0.84   0.401    -.0357651    .0892911
          white_aa2 |    .024429   .0316234     0.77   0.440    -.0376156    .0864735
          white_aa3 |    .041155   .0287921     1.43   0.153    -.0153346    .0976446
          black_aa1 |   .1037363   .0276308     3.75   0.000     .0495252    .1579474
          black_aa2 |   .0483537   .0310364     1.56   0.120    -.0125391    .1092466
          black_aa3 |   .0390654   .0304381     1.28   0.200    -.0206538    .0987845
           cand_age |    .000605   .0012377     0.49   0.625    -.0018232    .0030333
              _cons |   .5455025   .0724342     7.53   0.000     .4033879    .6876171
-------------------------------------------------------------------------------------
note: zero_sex omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      1,025
                                                F(16, 1008)       =       1.95
                                                Prob > F          =     0.0135
                                                R-squared         =     0.0279
                                                Root MSE          =     .26455

-------------------------------------------------------------------------------------
                    |               Robust
         out_ideo_7 | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |   .0072658   .0165746     0.44   0.661    -.0252588    .0397904
           zero_sex |          0  (omitted)
 cand_policy_abort1 |   .0752825   .0266847     2.82   0.005     .0229186    .1276465
 cand_policy_abort2 |   .0389569   .0250797     1.55   0.121    -.0102575    .0881712
   cand_policy_tax1 |   .0082618   .0237173     0.35   0.728    -.0382791    .0548027
   cand_policy_tax2 |  -.0223586   .0259199    -0.86   0.389    -.0732217    .0285045
cand_policy_health1 |    .031968   .0256364     1.25   0.213    -.0183388    .0822747
cand_policy_health2 |   .0587221   .0251284     2.34   0.020     .0094121     .108032
   cand_policy_eco1 |   .0186017   .0230799     0.81   0.420    -.0266886    .0638919
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          black_aa0 |   .0391935   .0342281     1.15   0.252     -.027973      .10636
          white_aa1 |   .0045649   .0337287     0.14   0.892    -.0616216    .0707513
          white_aa2 |   .0354649   .0349988     1.01   0.311    -.0332141    .1041438
          white_aa3 |  -.0345581     .03374    -1.02   0.306    -.1007669    .0316507
          black_aa1 |   .0459756   .0334934     1.37   0.170    -.0197492    .1117004
          black_aa2 |   .0140376     .03605     0.39   0.697     -.056704    .0847792
          black_aa3 |   .0122363    .033908     0.36   0.718     -.054302    .0787746
           cand_age |  -.0025442   .0013571    -1.87   0.061    -.0052071    .0001188
              _cons |   .7476154   .0803309     9.31   0.000     .5899806    .9052503
-------------------------------------------------------------------------------------
note: zero_sex omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      1,106
                                                F(15, 1090)       =       1.62
                                                Prob > F          =     0.0628
                                                R-squared         =     0.0213
                                                Root MSE          =     .34668

-------------------------------------------------------------------------------------
                    |               Robust
    out_priority_sj | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |  -.0041683   .0210123    -0.20   0.843    -.0453975    .0370608
           zero_sex |          0  (omitted)
 cand_policy_abort1 |  -.0214852   .0319682    -0.67   0.502    -.0842114    .0412411
 cand_policy_abort2 |  -.0225747   .0338025    -0.67   0.504    -.0889001    .0437506
   cand_policy_tax1 |   .0228876   .0338503     0.68   0.499    -.0435316    .0893068
   cand_policy_tax2 |   .0247276   .0320924     0.77   0.441    -.0382422    .0876975
cand_policy_health1 |  -.0157977   .0320057    -0.49   0.622    -.0785975    .0470021
cand_policy_health2 |  -.0123743   .0351959    -0.35   0.725    -.0814336    .0566851
   cand_policy_eco1 |   .0132963   .0294819     0.45   0.652    -.0445514    .0711439
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          black_aa0 |    .029416   .0408528     0.72   0.472     -.050743     .109575
          white_aa1 |   .0606091   .0419048     1.45   0.148    -.0216141    .1428323
          white_aa2 |   .0726188   .0432887     1.68   0.094    -.0123198    .1575575
          white_aa3 |   .0149449   .0406743     0.37   0.713    -.0648639    .0947537
          black_aa1 |   .1284805   .0411566     3.12   0.002     .0477254    .2092356
          black_aa2 |   .0999796   .0412147     2.43   0.015     .0191104    .1808487
          black_aa3 |   .1175021   .0413952     2.84   0.005     .0362788    .1987254
              _cons |   .6019291   .0539633    11.15   0.000     .4960455    .7078127
-------------------------------------------------------------------------------------
note: zero_sex omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      1,021
                                                F(15, 1005)       =       1.83
                                                Prob > F          =     0.0265
                                                R-squared         =     0.0253
                                                Root MSE          =     .35799

-------------------------------------------------------------------------------------
                    |               Robust
    out_priority_sj | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |  -.0381022   .0224672    -1.70   0.090    -.0821902    .0059857
           zero_sex |          0  (omitted)
 cand_policy_abort1 |   .0078422   .0360451     0.22   0.828      -.06289    .0785745
 cand_policy_abort2 |   .0400517   .0348679     1.15   0.251    -.0283704    .1084739
   cand_policy_tax1 |   .0067166   .0346905     0.19   0.847    -.0613575    .0747908
   cand_policy_tax2 |  -.0097207   .0345172    -0.28   0.778    -.0774547    .0580132
cand_policy_health1 |   .0211358   .0343501     0.62   0.538    -.0462703    .0885419
cand_policy_health2 |   .0378302   .0352377     1.07   0.283    -.0313177    .1069782
   cand_policy_eco1 |    .042021   .0320331     1.31   0.190    -.0208384    .1048804
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          black_aa0 |   .0175883   .0464835     0.38   0.705    -.0736277    .1088042
          white_aa1 |   .0464379   .0457485     1.02   0.310    -.0433356    .1362115
          white_aa2 |   .0558375   .0469436     1.19   0.235    -.0362812    .1479562
          white_aa3 |    .047565   .0438265     1.09   0.278    -.0384369    .1335669
          black_aa1 |    .171824   .0437439     3.93   0.000     .0859842    .2576638
          black_aa2 |   .0777983   .0455887     1.71   0.088    -.0116616    .1672581
          black_aa3 |   .0931542   .0430316     2.16   0.031     .0087121    .1775962
              _cons |   .5593074   .0567786     9.85   0.000     .4478893    .6707256
-------------------------------------------------------------------------------------
note: zero_sex omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      1,109
                                                F(15, 1093)       =       1.92
                                                Prob > F          =     0.0178
                                                R-squared         =     0.0258
                                                Root MSE          =     .37253

-------------------------------------------------------------------------------------
                    |               Robust
    out_fair_bwdiff | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |    .025978   .0226163     1.15   0.251    -.0183982    .0703542
           zero_sex |          0  (omitted)
 cand_policy_abort1 |  -.0091506   .0343892    -0.27   0.790     -.076627    .0583258
 cand_policy_abort2 |  -.0249857   .0357863    -0.70   0.485    -.0952033    .0452319
   cand_policy_tax1 |   .0258178   .0354278     0.73   0.466    -.0436964     .095332
   cand_policy_tax2 |   .0130156   .0319855     0.41   0.684    -.0497443    .0757756
cand_policy_health1 |  -.0026999   .0333815    -0.08   0.936    -.0681989    .0627991
cand_policy_health2 |  -.0104028   .0388942    -0.27   0.789    -.0867184    .0659129
   cand_policy_eco1 |   .0307231   .0323654     0.95   0.343    -.0327822    .0942284
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          black_aa0 |   .0872332   .0400078     2.18   0.029     .0087325     .165734
          white_aa1 |   .0673843   .0489391     1.38   0.169    -.0286409    .1634095
          white_aa2 |   .0702348   .0429508     1.64   0.102    -.0140405      .15451
          white_aa3 |  -.0214628     .04031    -0.53   0.595    -.1005566     .057631
          black_aa1 |    .139062   .0433868     3.21   0.001     .0539312    .2241929
          black_aa2 |   .1194579   .0447122     2.67   0.008     .0317263    .2071894
          black_aa3 |   .1129999   .0423412     2.67   0.008     .0299207    .1960791
              _cons |  -.0160981   .0554267    -0.29   0.772    -.1248528    .0926566
-------------------------------------------------------------------------------------
note: zero_sex omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      1,024
                                                F(15, 1008)       =       3.24
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0482
                                                Root MSE          =     .39191

-------------------------------------------------------------------------------------
                    |               Robust
    out_fair_bwdiff | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |   .0514719   .0246928     2.08   0.037     .0030167    .0999271
           zero_sex |          0  (omitted)
 cand_policy_abort1 |   .0388858   .0407157     0.96   0.340    -.0410113     .118783
 cand_policy_abort2 |   .0371025   .0366565     1.01   0.312    -.0348292    .1090342
   cand_policy_tax1 |   .0122783   .0383831     0.32   0.749    -.0630416    .0875982
   cand_policy_tax2 |   .0622675   .0373519     1.67   0.096    -.0110288    .1355638
cand_policy_health1 |    .053757   .0373247     1.44   0.150     -.019486    .1269999
cand_policy_health2 |   .0862287   .0426151     2.02   0.043     .0026043    .1698531
   cand_policy_eco1 |   .0444135   .0347577     1.28   0.202    -.0237922    .1126193
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          black_aa0 |   .1164595   .0492538     2.36   0.018     .0198078    .2131112
          white_aa1 |   .1214787    .047696     2.55   0.011     .0278839    .2150734
          white_aa2 |   .0820772   .0537328     1.53   0.127    -.0233638    .1875182
          white_aa3 |  -.0256753   .0498669    -0.51   0.607    -.1235301    .0721795
          black_aa1 |   .2119981   .0494386     4.29   0.000     .1149837    .3090124
          black_aa2 |   .1950928   .0520592     3.75   0.000     .0929359    .2972497
          black_aa3 |   .1187518   .0485445     2.45   0.015     .0234919    .2140117
              _cons |  -.1167915   .0622237    -1.88   0.061    -.2388944    .0053113
-------------------------------------------------------------------------------------
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(file fig_ep.gph not found)
file fig_ep.gph saved

.         
.         graph combine fig_rr.gph fig_ep.gph, row(2) imargin(vsmall)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)

. 
.         graph export figure_A1.png, as(png) replace
(file figure_A1.png not found)
file figure_A1.png saved as PNG format

.         
.         
.         
. //----------------- Table A1 (Demographics)
. 
. // Study 1
.         use data_study_1.dta, clear

. 
.         keep  r_* hhi_* male female edu_* reg_*

.         drop r_pid r_other

. 
.         gen total = 1

.         d, varlist

Contains data from data_study_1.dta
 Observations:         2,467                  
    Variables:            27                  22 Aug 2024 10:49
----------------------------------------------------------------------------------------------------------
Variable      Storage   Display    Value
    name         type    format    label      Variable label
----------------------------------------------------------------------------------------------------------
r_age           float   %9.0g                 
male            float   %9.0g                 
female          float   %9.0g                 
hhi_1           float   %9.0g                 
hhi_2           float   %9.0g                 
hhi_3           float   %9.0g                 
hhi_4           float   %9.0g                 
hhi_5           float   %9.0g                 
hhi_6           float   %9.0g                 
edu_nohs        float   %9.0g                 
edu_hs          float   %9.0g                 
edu_somecol     float   %9.0g                 
edu_2yr         float   %9.0g                 
edu_ba          float   %9.0g                 
edu_postgrad    float   %9.0g                 
reg_ne          float   %9.0g                 
reg_mw          float   %9.0g                 
reg_s           float   %9.0g                 
reg_w           float   %9.0g                 
r_white         float   %9.0g                 
r_black         float   %9.0g                 
r_asian         float   %9.0g                 
r_hispanic      float   %9.0g                 
r_dem           float   %9.0g                 Respondent PID, Democrats (Incl. Leaners)
r_ind           float   %9.0g                 Respondent PID, Pure Independents
r_gop           float   %9.0g                 Respondent PID, Republicans (Incl. Leaners)
total           float   %9.0g                 
----------------------------------------------------------------------------------------------------------
Sorted by: 
     Note: Dataset has changed since last saved.

.         foreach v of varlist `r(varlist)' {
  2.                 //loc var = subinstr("`v'", "x_", "", .)
.                 gen n_`v' = `v' 
  3.                 gen m_`v' = `v'
  4.         }

.                 
.         collapse (sum) n_* (mean) m_*

.         gen i = .
(1 missing value generated)

.         reshape long n_ m_, i(i) j(x) s
(j = edu_2yr edu_ba edu_hs edu_nohs edu_postgrad edu_somecol female hhi_1 hhi_2 hhi_3 hhi_4 hhi_5 hhi_6 ma
> le r_age r_asian r_black r_dem r_gop r_hispanic r_ind r_white reg_mw reg_ne reg_s reg_w total)

Data                               Wide   ->   Long
-----------------------------------------------------------------------------
Number of observations                1   ->   27          
Number of variables                  55   ->   4           
j variable (27 values)                    ->   x
xij variables:
         n_edu_2yr n_edu_ba ... n_total   ->   n_
         m_edu_2yr m_edu_ba ... m_total   ->   m_
-----------------------------------------------------------------------------

.         drop i

.                 
.         
.         replace n = . if x == "r_age"
(1 real change made, 1 to missing)

.         replace m = . if x == "total"
(1 real change made, 1 to missing)

.         
.         gen var = x

.         replace var = "Age" if x == "r_age"
(1 real change made)

.         replace var = "Democrat" if x == "r_dem"
(1 real change made)

.         replace var = "Republican" if x == "r_gop"
(1 real change made)

.         replace var = "Independent" if x == "r_ind"
(1 real change made)

.         replace var = "Other" if x == "r_oth"
(0 real changes made)

.         replace var = "< High School" if x == "edu_nohs"
variable var was str12 now str13
(1 real change made)

.         replace var = "High School Diploma" if x == "edu_hs"
variable var was str13 now str19
(1 real change made)

.         replace var = "Some College" if x == "edu_somecol"
(1 real change made)

.         replace var = "Associate's" if x == "edu_2yr"
(1 real change made)

.         replace var = "Bachelor's" if x == "edu_ba"
(1 real change made)

.         replace var = "Postgraduate" if x == "edu_postgrad"
(1 real change made)

.         replace var = "< $30,000" if x == "hhi_1"
(1 real change made)

.         replace var = "$30,000 - $59,999" if x == "hhi_2"
(1 real change made)

.         replace var = "$60,000 - $99,999" if x == "hhi_3"
(1 real change made)

.         replace var = "$100,00 - $200,000" if x == "hhi_4"
(1 real change made)

.         replace var = "$250,000+" if x == "hhi_5"
(1 real change made)

.         replace var = "Prefer not to say" if x == "hhi_6"
(1 real change made)

.         replace var = "Northeast" if x == "reg_ne"
(1 real change made)

.         replace var = "Midwest" if x == "reg_mw"
(1 real change made)

.         replace var = "South" if x == "reg_s"
(1 real change made)

.         replace var = "West" if x == "reg_w"
(1 real change made)

.         replace var = "White" if x == "r_white"
(1 real change made)

.         replace var = "Black" if x == "r_black"
(1 real change made)

.         replace var = "Asian" if x == "r_asian"
(1 real change made)

.         replace var = "Hispanic" if x == "r_hispanic"
(1 real change made)

.         replace var = proper(var)
(6 real changes made)

.         
.         rename n n_study1

.         rename m m_study1

.         
.         tempfile temp

.         save `temp', replace
(file C:\Users\wujen\AppData\Local\Temp\ST_310c_000001.tmp not found)
file C:\Users\wujen\AppData\Local\Temp\ST_310c_000001.tmp saved as .dta format

.         
. 
. // Study 2
.         insheet using study_2_raw.csv, comma name clear
(179 vars, 1,858 obs)

. 
.         keep if acq_pass == "1" | acq_identity == "Because he left his ID"
(411 observations deleted)

.                 
.         // Qualtrics demographics
.         gen r_age = 2021 - real(dem_birth)
(3 missing values generated)

.         
.         // Respondent Race
.         gen r_white = dem_race == "White"

.         gen r_black = dem_race == "Black or African American"

.         gen r_asian = dem_race == "Asian"

.         gen r_hispanic = dem_race == "Hispanic or Latino"

.         gen r_other = missing(r_white) & missing(r_black) & missing(r_asian) & missing(r_hispanic)

.         
.         // Party
.         gen r_dem = dem_pid == "Democrat"

.         gen r_gop = dem_pid == "Republican"

.         gen r_ind = dem_pid == "Independent"

.         gen r_oth = dem_pid == "Other"

.         
.         label var r_dem "Respondent PID, Democrats (Incl. Leaners)"

.         label var r_ind "Respondent PID, Pure Independents"

.         label var r_gop "Respondent PID, Republicans (Incl. Leaners)"

.         label var dem_pid "Respondent PID from Qualtrics"

. 
.         gen male = gender == "1"

.         gen female = gender == "2"

. 
.         gen temp = real(hhi)
(45 missing values generated)

.         drop hhi

.         rename temp hhi

.         gen hhi_1 = inrange(hhi, 1, 4) // <30k

.         gen hhi_2 = inrange(hhi, 5, 10) // 30-60k

.         gen hhi_3 = inrange(hhi, 11, 18) // 60-100k

.         gen hhi_4 = inlist(hhi, 19, 20, 21, 22) // 100-200k

.         gen hhi_5 = inlist(hhi, 23, 24) // 200+

.         gen hhi_6 = hhi == -3105 // prefer not say

. 
.         gen temp = real(educ)
(138 missing values generated)

.         drop educ

.         rename temp educ

.         gen edu_nohs = educ == 1

.         gen edu_hs = inlist(educ, 2, 3)

.         gen edu_somecol = educ == 4

.         gen edu_2yr = educ == 5

.         gen edu_ba = educ == 6

.         gen edu_postgrad = inlist(educ, 7, 8)

. 
.         gen temp = real(region)
(2 missing values generated)

.         drop region

.         rename temp region

.         gen reg_ne = region == 1

.         gen reg_mw = region == 2

.         gen reg_s = region == 3

.         gen reg_w = region == 4

.                 
.         keep  r_* hhi_* male female edu_* reg_*

.         drop r_other r_id

. 
.         gen total = 1

.         d, varlist

Contains data
 Observations:         1,447                  
    Variables:            28                  
----------------------------------------------------------------------------------------------------------
Variable      Storage   Display    Value
    name         type    format    label      Variable label
----------------------------------------------------------------------------------------------------------
r_age           float   %9.0g                 
r_white         float   %9.0g                 
r_black         float   %9.0g                 
r_asian         float   %9.0g                 
r_hispanic      float   %9.0g                 
r_dem           float   %9.0g                 Respondent PID, Democrats (Incl. Leaners)
r_gop           float   %9.0g                 Respondent PID, Republicans (Incl. Leaners)
r_ind           float   %9.0g                 Respondent PID, Pure Independents
r_oth           float   %9.0g                 
male            float   %9.0g                 
female          float   %9.0g                 
hhi_1           float   %9.0g                 
hhi_2           float   %9.0g                 
hhi_3           float   %9.0g                 
hhi_4           float   %9.0g                 
hhi_5           float   %9.0g                 
hhi_6           float   %9.0g                 
edu_nohs        float   %9.0g                 
edu_hs          float   %9.0g                 
edu_somecol     float   %9.0g                 
edu_2yr         float   %9.0g                 
edu_ba          float   %9.0g                 
edu_postgrad    float   %9.0g                 
reg_ne          float   %9.0g                 
reg_mw          float   %9.0g                 
reg_s           float   %9.0g                 
reg_w           float   %9.0g                 
total           float   %9.0g                 
----------------------------------------------------------------------------------------------------------
Sorted by: 
     Note: Dataset has changed since last saved.

.         foreach v of varlist `r(varlist)' {
  2.                 //loc var = subinstr("`v'", "x_", "", .)
.                 gen n_`v' = `v' 
  3.                 gen m_`v' = `v'
  4.         }
(3 missing values generated)
(3 missing values generated)

.                 
.         collapse (sum) n_* (mean) m_*

.         gen i = .
(1 missing value generated)

.         reshape long n_ m_, i(i) j(x) s
(j = edu_2yr edu_ba edu_hs edu_nohs edu_postgrad edu_somecol female hhi_1 hhi_2 hhi_3 hhi_4 hhi_5 hhi_6 ma
> le r_age r_asian r_black r_dem r_gop r_hispanic r_ind r_oth r_white reg_mw reg_ne reg_s reg_w total)

Data                               Wide   ->   Long
-----------------------------------------------------------------------------
Number of observations                1   ->   28          
Number of variables                  57   ->   4           
j variable (28 values)                    ->   x
xij variables:
         n_edu_2yr n_edu_ba ... n_total   ->   n_
         m_edu_2yr m_edu_ba ... m_total   ->   m_
-----------------------------------------------------------------------------

.         drop i

.         
.         replace n = . if x == "r_age"
(1 real change made, 1 to missing)

.         replace m = . if x == "total"
(1 real change made, 1 to missing)

. 
.         gen var = x

.         replace var = "Age" if x == "r_age"
(1 real change made)

.         replace var = "Democrat" if x == "r_dem"
(1 real change made)

.         replace var = "Republican" if x == "r_gop"
(1 real change made)

.         replace var = "Independent" if x == "r_ind"
(1 real change made)

.         replace var = "Other" if x == "r_oth"
(1 real change made)

.         replace var = "< High School" if x == "edu_nohs"
variable var was str12 now str13
(1 real change made)

.         replace var = "High School Diploma" if x == "edu_hs"
variable var was str13 now str19
(1 real change made)

.         replace var = "Some College" if x == "edu_somecol"
(1 real change made)

.         replace var = "Associate's" if x == "edu_2yr"
(1 real change made)

.         replace var = "Bachelor's" if x == "edu_ba"
(1 real change made)

.         replace var = "Postgraduate" if x == "edu_postgrad"
(1 real change made)

.         replace var = "< $30,000" if x == "hhi_1"
(1 real change made)

.         replace var = "$30,000 - $59,999" if x == "hhi_2"
(1 real change made)

.         replace var = "$60,000 - $99,999" if x == "hhi_3"
(1 real change made)

.         replace var = "$100,00 - $200,000" if x == "hhi_4"
(1 real change made)

.         replace var = "$250,000+" if x == "hhi_5"
(1 real change made)

.         replace var = "Prefer not to say" if x == "hhi_6"
(1 real change made)

.         replace var = "Northeast" if x == "reg_ne"
(1 real change made)

.         replace var = "Midwest" if x == "reg_mw"
(1 real change made)

.         replace var = "South" if x == "reg_s"
(1 real change made)

.         replace var = "West" if x == "reg_w"
(1 real change made)

.         replace var = "White" if x == "r_white"
(1 real change made)

.         replace var = "Black" if x == "r_black"
(1 real change made)

.         replace var = "Asian" if x == "r_asian"
(1 real change made)

.         replace var = "Hispanic" if x == "r_hispanic"
(1 real change made)

.         replace var = proper(var)
(6 real changes made)

.         
.         rename n n_study2

.         rename m m_study2

.         
. 
.         cap drop _m

.         merge 1:1 x using `temp'

    Result                      Number of obs
    -----------------------------------------
    Not matched                             1
        from master                         1  (_merge==1)
        from using                          0  (_merge==2)

    Matched                                27  (_merge==3)
    -----------------------------------------

. 
.         gen order = .
(28 missing values generated)

.         replace order = 0.1 if x == "r_white"
(1 real change made)

.         replace order = 0.2 if x == "r_black"
(1 real change made)

.         replace order = 0.3 if x == "r_asian"
(1 real change made)

.         replace order = 0.4 if x == "r_hispanic"
(1 real change made)

.         replace order = 1 if x == "r_age"
(1 real change made)

.         replace order = 2 if x == "female"
(1 real change made)

.         replace order = 3 if x == "male"
(1 real change made)

.         replace order = 4 if x == "r_dem"
(1 real change made)

.         replace order = 5 if x == "r_gop"
(1 real change made)

.         replace order = 6 if x == "r_ind"
(1 real change made)

.         replace order = 7 if x == "r_oth"
(1 real change made)

.         replace order = 8 if x == "edu_nohs"
(1 real change made)

.         replace order = 9 if x == "edu_hs"
(1 real change made)

.         replace order = 10 if x == "edu_somecol"
(1 real change made)

.         replace order = 11 if x == "edu_2yr"
(1 real change made)

.         replace order = 12 if x == "edu_ba"
(1 real change made)

.         replace order = 13 if x == "edu_postgrad"
(1 real change made)

.         replace order = 14 if x == "hhi_1"
(1 real change made)

.         replace order = 15 if x == "hhi_2"
(1 real change made)

.         replace order = 16 if x == "hhi_3"
(1 real change made)

.         replace order = 17 if x == "hhi_4"
(1 real change made)

.         replace order = 18 if x == "hhi_5"
(1 real change made)

.         replace order = 19 if x == "hhi_6"
(1 real change made)

.         replace order = 20 if x == "reg_ne"
(1 real change made)

.         replace order = 21 if x == "reg_mw"
(1 real change made)

.         replace order = 22 if x == "reg_s"
(1 real change made)

.         replace order = 23 if x == "reg_w"
(1 real change made)

.         replace order = 24 if x == "total"
(1 real change made)

.         
.         order var n_study1 m_study1 n_study2 m_study2

.         sort order 

.         drop x _m order

.         list

     +-----------------------------------------------------------------+
     |                 var   n_study1   m_study1   n_study2   m_study2 |
     |-----------------------------------------------------------------|
  1. |               White       1702   .6899068       1060   .7325501 |
  2. |               Black        337   .1366032        203   .1402903 |
  3. |               Asian        114     .04621         56   .0387008 |
  4. |            Hispanic        185   .0749899         76   .0525225 |
  5. |                 Age          .   44.90799          .   12.21884 |
     |-----------------------------------------------------------------|
  6. |              Female       1294   .5245237        783   .5411196 |
  7. |                Male       1173   .4754763        664   .4588805 |
  8. |            Democrat       1106   .4483178        548   .3787146 |
  9. |          Republican        993   .4025132        455   .3144437 |
 10. |         Independent        230   .0932306        395   .2729786 |
     |-----------------------------------------------------------------|
 11. |               Other          .          .         49   .0338632 |
 12. |       < High School         98   .0397244          2   .0013822 |
 13. | High School Diploma        634   .2569923        273   .1886662 |
 14. |        Some College        447   .1811917        145   .1002073 |
 15. |         Associate'S        258   .1045805        104   .0718728 |
     |-----------------------------------------------------------------|
 16. |          Bachelor'S        584   .2367248        285   .1969592 |
 17. |        Postgraduate        423   .1714633        347   .2398065 |
 18. |           < $30,000        891   .3611674        318    .219765 |
 19. |   $30,000 - $59,999        565   .2290231        499   .3448514 |
 20. |   $60,000 - $99,999        435   .1763275        319   .2204561 |
     |-----------------------------------------------------------------|
 21. |  $100,00 - $200,000        340   .1378192        170   .1174845 |
 22. |           $250,000+        104   .0421565         48   .0331721 |
 23. |   Prefer Not To Say        132   .0535063          2   .0013822 |
 24. |           Northeast        504   .2042967        263   .1817553 |
 25. |             Midwest        476   .1929469        350   .2418797 |
     |-----------------------------------------------------------------|
 26. |               South        934   .3785975        616   .4257084 |
 27. |                West        553   .2241589        216   .1492744 |
 28. |               Total       2467          .       1447          . |
     +-----------------------------------------------------------------+

. 
.         outsheet using table_a1.csv, comma replace
(file table_a1.csv not found)

. 
. 
end of do-file

. do 6_appendix_figure_s1.do

. 
. use data_study_1.dta, clear

. 
. 
. // Set omitted categories
.         gen zero_race = 0

.         label var zero_race "White"

.         gen zero_sex = 0

.         label var zero_sex "Male"

.         gen zero_eco = 0

.         label var zero_eco "Maintain investment in energy"

.         
. // Set regression variables
.         loc reg_race "cand_black zero_race"

.         loc reg_sex "cand_female zero_sex"

.         loc reg_issues "cand_policy_abort1 cand_policy_abort2 cand_policy_tax1 cand_policy_tax2"

.         loc reg_issues "`reg_issues' cand_policy_health1 cand_policy_health2 cand_policy_eco1 zero_eco"

.         loc reg_affirm "cand_policy_aa1 cand_policy_aa2 cand_policy_aa3"

.         
. // Interactive Terms for Black Candidate X Affirmative Action
.         gen noracepolicy = cand_policy_aa1 == 0 & cand_policy_aa2 == 0 & cand_policy_aa3 == 0   

.         gen black_aa1 = cand_policy_aa1*cand_black

.         gen black_aa2 = cand_policy_aa2*cand_black

.         gen black_aa3 = cand_policy_aa3*cand_black

.         gen white_aa1 = cand_policy_aa1*cand_white

.         gen white_aa2 = cand_policy_aa2*cand_white

.         gen white_aa3 = cand_policy_aa3*cand_white

.         gen black_aa0 = noracepolicy*cand_black

.         gen white_aa0 = noracepolicy*cand_white

.         label var black_aa0 "Black X No Position"

.         label var white_aa0 "White X No Position"

.         label var black_aa1 "Black X Expand (race)"

.         label var black_aa2 "Black X Keep as is"

.         label var black_aa3 "Black X Replace (class)"

.         label var white_aa1 "White X Expand (race)"

.         label var white_aa2 "White X Keep as is"

.         label var white_aa3 "White X Replace (class)"

.         replace white_aa0 = 0
(294 real changes made)

.         label var noracepolicy "Not shown position"

.         loc int "white_aa0 black_aa0 white_aa1 white_aa2 white_aa3 black_aa1 black_aa2 black_aa3"

.         
. 
. //============================================================================== Liberalness
. 
. 
.         // Panel (i)
.                 reg out_ideo_econ `reg_sex' `reg_issues' `int' cand_age, robust
note: zero_sex omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      2,308
                                                F(16, 2291)       =       2.65
                                                Prob > F          =     0.0004
                                                R-squared         =     0.0189
                                                Root MSE          =     .26063

-------------------------------------------------------------------------------------
                    |               Robust
      out_ideo_econ | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |   .0079334   .0108527     0.73   0.465    -.0133487    .0292155
           zero_sex |          0  (omitted)
 cand_policy_abort1 |   .0646346   .0173989     3.71   0.000     .0305154    .0987538
 cand_policy_abort2 |   .0418276   .0171087     2.44   0.015     .0082775    .0753778
   cand_policy_tax1 |   .0664907   .0170762     3.89   0.000     .0330043    .0999771
   cand_policy_tax2 |    .011252    .017033     0.66   0.509    -.0221498    .0446538
cand_policy_health1 |   .0603804   .0165252     3.65   0.000     .0279744    .0927863
cand_policy_health2 |   .0551035   .0174545     3.16   0.002     .0208751    .0893318
   cand_policy_eco1 |   .0241842   .0155537     1.55   0.120    -.0063167     .054685
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          black_aa0 |   .0193607   .0211538     0.92   0.360    -.0221218    .0608432
          white_aa1 |     .02285   .0220619     1.04   0.300    -.0204134    .0661134
          white_aa2 |    .017954   .0221859     0.81   0.418    -.0255526    .0614605
          white_aa3 |  -.0081406   .0209523    -0.39   0.698    -.0492282    .0329469
          black_aa1 |   .0561444   .0214127     2.62   0.009     .0141542    .0981347
          black_aa2 |    .021707   .0221684     0.98   0.328    -.0217652    .0651792
          black_aa3 |  -.0014847   .0212453    -0.07   0.944    -.0431467    .0401774
           cand_age |   .0002842   .0009025     0.31   0.753    -.0014856    .0020539
              _cons |    .541066   .0534373    10.13   0.000     .4362754    .6458566
-------------------------------------------------------------------------------------

.                 eststo ideo_econ

.                 reg out_ideo_soc `reg_sex' `reg_issues' `int' cand_age, robust
note: zero_sex omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      2,310
                                                F(16, 2293)       =       2.71
                                                Prob > F          =     0.0003
                                                R-squared         =     0.0193
                                                Root MSE          =     .26368

-------------------------------------------------------------------------------------
                    |               Robust
       out_ideo_soc | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |   .0157763   .0110009     1.43   0.152    -.0057964     .037349
           zero_sex |          0  (omitted)
 cand_policy_abort1 |   .0772901   .0175177     4.41   0.000     .0429378    .1116423
 cand_policy_abort2 |    .042174   .0172457     2.45   0.015     .0083552    .0759929
   cand_policy_tax1 |   .0283453   .0168639     1.68   0.093    -.0047247    .0614153
   cand_policy_tax2 |  -.0030549   .0171749    -0.18   0.859    -.0367349    .0306251
cand_policy_health1 |   .0344615   .0167695     2.06   0.040     .0015766    .0673464
cand_policy_health2 |   .0240626   .0175912     1.37   0.171    -.0104337     .058559
   cand_policy_eco1 |  -.0045148   .0156412    -0.29   0.773    -.0351871    .0261575
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          black_aa0 |   .0287829   .0213778     1.35   0.178    -.0131389    .0707047
          white_aa1 |   .0336419   .0225097     1.49   0.135    -.0104996    .0777834
          white_aa2 |   .0252512   .0226658     1.11   0.265    -.0191964    .0696988
          white_aa3 |   .0049589   .0214781     0.23   0.817    -.0371597    .0470775
          black_aa1 |    .051472   .0222196     2.32   0.021     .0078994    .0950446
          black_aa2 |   .0305656   .0231191     1.32   0.186    -.0147711    .0759022
          black_aa3 |  -.0027621   .0219649    -0.13   0.900    -.0458352     .040311
           cand_age |   -.000509   .0009102    -0.56   0.576     -.002294    .0012759
              _cons |   .6297959   .0545289    11.55   0.000     .5228649     .736727
-------------------------------------------------------------------------------------

.                 eststo ideo_soc

.                 
.         // Panel (ii)
.                 reg out_policy_tanf `reg_sex' `reg_issues' `int' cand_age, robust
note: zero_sex omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      2,171
                                                F(16, 2154)       =       0.94
                                                Prob > F          =     0.5220
                                                R-squared         =     0.0067
                                                Root MSE          =     .33158

-------------------------------------------------------------------------------------
                    |               Robust
    out_policy_tanf | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |   .0148267   .0142705     1.04   0.299    -.0131588    .0428121
           zero_sex |          0  (omitted)
 cand_policy_abort1 |  -.0174082   .0221734    -0.79   0.432    -.0608917    .0260752
 cand_policy_abort2 |  -.0086157   .0219665    -0.39   0.695    -.0516935    .0344621
   cand_policy_tax1 |  -.0178624   .0224234    -0.80   0.426    -.0618361    .0261113
   cand_policy_tax2 |   .0007174   .0221931     0.03   0.974    -.0428048    .0442396
cand_policy_health1 |  -.0231732    .022512    -1.03   0.303    -.0673207    .0209743
cand_policy_health2 |  -.0118236   .0230127    -0.51   0.607    -.0569529    .0333058
   cand_policy_eco1 |  -.0115004   .0201381    -0.57   0.568    -.0509926    .0279918
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          black_aa0 |  -.0432081   .0267618    -1.61   0.107    -.0956897    .0092734
          white_aa1 |  -.0459029   .0290157    -1.58   0.114    -.1028046    .0109987
          white_aa2 |  -.0260136   .0288477    -0.90   0.367    -.0825858    .0305585
          white_aa3 |  -.0556437    .027253    -2.04   0.041    -.1090887   -.0021987
          black_aa1 |   .0060111   .0280706     0.21   0.830    -.0490372    .0610593
          black_aa2 |  -.0294802   .0293296    -1.01   0.315    -.0869975     .028037
          black_aa3 |   .0091809   .0269937     0.34   0.734    -.0437556    .0621174
           cand_age |  -.0002982   .0011986    -0.25   0.804    -.0026488    .0020524
              _cons |   .7344416   .0705517    10.41   0.000      .596085    .8727982
-------------------------------------------------------------------------------------

.                         eststo policy_tanf

.                 reg out_policy_minwage `reg_sex' `reg_issues' `int' cand_age, robust
note: zero_sex omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      2,170
                                                F(16, 2153)       =       1.38
                                                Prob > F          =     0.1403
                                                R-squared         =     0.0104
                                                Root MSE          =     .37502

-------------------------------------------------------------------------------------
                    |               Robust
 out_policy_minwage | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |  -.0106254   .0161448    -0.66   0.511    -.0422865    .0210357
           zero_sex |          0  (omitted)
 cand_policy_abort1 |    .008032   .0254184     0.32   0.752    -.0418153    .0578792
 cand_policy_abort2 |   .0444927   .0259206     1.72   0.086    -.0063394    .0953248
   cand_policy_tax1 |   .0316405   .0246601     1.28   0.200    -.0167196    .0800007
   cand_policy_tax2 |   .0127792   .0249094     0.51   0.608    -.0360697    .0616282
cand_policy_health1 |   .0122685   .0248961     0.49   0.622    -.0365544    .0610915
cand_policy_health2 |   .0280823   .0259854     1.08   0.280    -.0228768    .0790415
   cand_policy_eco1 |   .0083818   .0231093     0.36   0.717    -.0369371    .0537008
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          black_aa0 |   .0586569   .0323096     1.82   0.070    -.0047045    .1220182
          white_aa1 |   .0309436   .0337124     0.92   0.359    -.0351686    .0970558
          white_aa2 |   .0618855    .034103     1.81   0.070    -.0049928    .1287638
          white_aa3 |  -.0323102   .0336053    -0.96   0.336    -.0982125    .0335921
          black_aa1 |   .0625871   .0333525     1.88   0.061    -.0028193    .1279936
          black_aa2 |   .0436779   .0338715     1.29   0.197    -.0227464    .1101021
          black_aa3 |    .045481   .0316458     1.44   0.151    -.0165785    .1075406
           cand_age |   .0012066   .0013121     0.92   0.358    -.0013665    .0037797
              _cons |   .5060981    .077739     6.51   0.000     .3536468    .6585493
-------------------------------------------------------------------------------------

.                         eststo policy_minwage

.                 reg out_policy_repar `reg_sex' `reg_issues' `int' cand_age, robust
note: zero_sex omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      2,168
                                                F(16, 2151)       =       1.38
                                                Prob > F          =     0.1404
                                                R-squared         =     0.0101
                                                Root MSE          =     .38844

-------------------------------------------------------------------------------------
                    |               Robust
   out_policy_repar | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |   .0063109   .0167358     0.38   0.706    -.0265091     .039131
           zero_sex |          0  (omitted)
 cand_policy_abort1 |    .045168   .0261454     1.73   0.084    -.0061049    .0964408
 cand_policy_abort2 |   .0436565    .026851     1.63   0.104    -.0090002    .0963132
   cand_policy_tax1 |   .0525841   .0260307     2.02   0.043      .001536    .1036321
   cand_policy_tax2 |   .0329944   .0260367     1.27   0.205    -.0180654    .0840542
cand_policy_health1 |   .0515058   .0260863     1.97   0.048     .0003487    .1026628
cand_policy_health2 |   .0644722   .0275692     2.34   0.019     .0104072    .1185372
   cand_policy_eco1 |   .0269201   .0238934     1.13   0.260    -.0199365    .0737767
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          black_aa0 |   .0382206   .0346633     1.10   0.270    -.0297565    .1061977
          white_aa1 |   .0021081   .0341369     0.06   0.951    -.0648366    .0690529
          white_aa2 |    .027003   .0343301     0.79   0.432    -.0403207    .0943268
          white_aa3 |  -.0605522   .0346589    -1.75   0.081    -.1285207    .0074163
          black_aa1 |   .0478978   .0334755     1.43   0.153    -.0177499    .1135455
          black_aa2 |    .024485   .0354347     0.69   0.490    -.0450049    .0939748
          black_aa3 |   .0102724   .0350153     0.29   0.769    -.0583949    .0789398
           cand_age |   .0001219   .0013794     0.09   0.930    -.0025831     .002827
              _cons |   .4139612   .0814002     5.09   0.000     .2543299    .5735926
-------------------------------------------------------------------------------------

.                         eststo policy_repar

.         
.         
. 
.         // i
.                 coefplot (ideo_econ, label() mc(gs4) ciopts(color(gs4) lw(med))) ///
>                                         , bylabel("{bf:(a) Economic Liberalness}") || ///
>                                  (ideo_soc, label() mc(gs4) ciopts(color(gs4) lw(med))) ///
>                                         , bylabel("{bf:(b) Social Liberalness}") ///
>                                 || , drop(_cons `reg_sex' `reg_issues' cand_age) omitted baselevels ms(c
> ) msize(med) ///
>                                 ylabel(,labsize(vsmall)) ///
>                         xline(0, lc(black)) nokey ///
>                         subtitle(, bcolor(white) color(black) size(vsmall)) ///
>                         byopts(row(1) t1title("{bf:(i) Inferred Liberalness by Dimension}", size(small))
> ) ///
>                         xtitle("Effects of Candidate Attributes (Scale 0 to 1)", size(vsmall)) ///
>                         xlabel(-0.2(0.1)0.2,labsize(small)) norecycle ///
>                         headings(white_aa0 = "{bf: No Affirmative Action}" ///
>                                 white_aa1 = "{bf: White Affirmative Action}" ///
>                                 black_aa1 = "{bf: Black X Affirmative Action}", labsize(vsmall)) saving(
> s1_1.gph, replace)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(file s1_1.gph not found)
file s1_1.gph saved

. 
.         // ii
.                 coefplot (policy_tanf, label() mc(gs4) ciopts(color(gs4) lw(med))) ///
>                                         , bylabel("{bf:(c) TANF}") || ///
>                                  (policy_minwage, label() mc(gs4) ciopts(color(gs4) lw(med))) ///
>                                         , bylabel("{bf:(d) Minimum Wage}") || ///
>                                 (policy_repar, label() mc(gs4) ciopts(color(gs4) lw(med))) ///
>                                         , bylabel("{bf:(e) Reparations}") ///
>                                 || , drop(_cons `reg_sex' `reg_issues' cand_age) omitted baselevels ms(c
> ) msize(med) ///
>                                 ylabel(,labsize(vsmall)) ///
>                         xline(0, lc(black)) nokey ///
>                         subtitle(, bcolor(white) color(black) size(vsmall)) ///
>                         byopts(row(1) t1title("{bf:(ii) Inferred Liberalness on Other Issues}", size(sma
> ll))) ///
>                         xtitle("Effects of Candidate Attributes (Scale 0 to 1)", size(vsmall)) ///
>                         xlabel(-0.2(0.1)0.2,labsize(small)) norecycle ///
>                         headings(white_aa0 = "{bf: No Affirmative Action}" ///
>                                 white_aa1 = "{bf: White Affirmative Action}" ///
>                                 black_aa1 = "{bf: Black X Affirmative Action}", labsize(vsmall)) saving(
> s1_2.gph, replace)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
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(file s1_2.gph not found)
file s1_2.gph saved

.                                 
.                 graph combine s1_1.gph s1_2.gph, rows(2) imargin(0)
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.                 
.         graph export figure_s1.png, as(png) replace
(file figure_s1.png not found)
file figure_s1.png saved as PNG format

. 
end of do-file

. do 7_appendix_figure_s2.do

. /*
>         Figure S2 Alternative favoritism codings
> */
. 
. use data_study_2.dta, clear

. 
. 
. // Set omitted categories
.         gen zero_race = 0

.         label var zero_race "White"

.         gen zero_sex = 0

.         label var zero_sex "Male"

.         gen zero_eco = 0

.         label var zero_eco "Maintain investment in energy"

.         gen zero_biden = 0

.         label var zero_biden "Vote Share: 51%"

.         gen zero_exp = 0

.         label var zero_exp "Political newcomer"

.         gen zero_dist = 0

.         label var zero_dist "[63, 8, 13, 11, 5]"

.         gen zero_racepol = 0

.         label var zero_racepol "Not shown policy"

.         
. // Set regression variables
.         loc reg_race "cand_black zero_race cand_asian cand_hispa"

.         loc reg_sex "cand_female zero_sex"

.         loc reg_exp "cand_exp_teach cand_exp_council cand_exp_lawyer cand_exp_business zero_exp"

.         loc reg_biden "cand_biden_p59 cand_biden_p57 cand_biden_p55 cand_biden_p53 zero_biden"

.         loc reg_distpop "cand_dist1 cand_dist2 cand_dist3 cand_dist4 cand_dist5 cand_dist6 zero_dist"

.         loc reg_issues "cand_policy_abort1 cand_policy_abort2 cand_policy_tax1 cand_policy_tax2"

.         loc reg_issues "`reg_issues' cand_policy_health1 cand_policy_health2 cand_policy_eco1 zero_eco"

.         loc reg_affirm "cand_policy_aa1 cand_policy_aa2 cand_policy_aa3 zero_racepol"

.         loc reg_affirm2 "noracepolicy cand_policy_aa1 cand_policy_aa2 cand_policy_aa3 "

.         
. // Interactive Terms for Black Candidate X Affirmative Action
.         gen noracepolicy = cand_policy_aa1 == 0 & cand_policy_aa2 == 0 & cand_policy_aa3 == 0   

.         
.         loc int ""

.         foreach r in white black asian hispa {
  2.                 gen `r'_aa1 = cand_policy_aa1*cand_`r'
  3.                 gen `r'_aa2 = cand_policy_aa2*cand_`r'
  4.                 gen `r'_aa3 = cand_policy_aa3*cand_`r'
  5.                 gen `r'_aa0 = noracepolicy*cand_`r'
  6.                 
.                 loc lab = proper("`r'")
  7.                 if "`lab'" == "Hispa" loc lab = "Hispanic"
  8.         
.                 label var `r'_aa0 "`lab' X No Position"
  9.                 label var `r'_aa1 "`lab' X Expand"
 10.                 label var `r'_aa2 "`lab' X Keep"
 11.                 label var `r'_aa3 "`lab' X End"
 12.                 
.                 loc int "`int' `r'_aa0 `r'_aa1 `r'_aa2 `r'_aa3"
 13.         }

.         
.         
.         // set reference
.         replace white_aa0 = 0
(560 real changes made)

.         label var noracepolicy "Not shown position"

.         
.         // Favoritism measures
.         gen out_fair_bwdiff = out_fair_black - out_fair_white
(2 missing values generated)

.         gen favor_black = out_fair_bwdiff > 0

.         gen favor_white = out_fair_bwdiff < 0

.         
. //============================================================================== Regress the things
.         // All attributes, pooled 
.                 eststo clear

.                 reg out_fair_bwdiff `reg_race' `reg_sex' cand_age `reg_exp' `reg_biden' `reg_distpop' `r
> eg_issues' `reg_affirm', vce(cluster r_id)
note: zero_race omitted because of collinearity.
note: zero_sex omitted because of collinearity.
note: zero_exp omitted because of collinearity.
note: zero_biden omitted because of collinearity.
note: zero_dist omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: zero_racepol omitted because of collinearity.

Linear regression                               Number of obs     =      7,233
                                                F(29, 1446)       =      14.04
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0653
                                                Root MSE          =     .37225

                                      (Std. err. adjusted for 1,447 clusters in r_id)
-------------------------------------------------------------------------------------
                    |               Robust
    out_fair_bwdiff | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
         cand_black |   .1984642   .0121063    16.39   0.000     .1747165    .2222118
          zero_race |          0  (omitted)
         cand_asian |   .0686829   .0099904     6.87   0.000     .0490858    .0882801
         cand_hispa |   .0768654   .0102886     7.47   0.000     .0566832    .0970477
        cand_female |    .014205   .0076036     1.87   0.062    -.0007103    .0291202
           zero_sex |          0  (omitted)
           cand_age |   -.000109   .0007101    -0.15   0.878    -.0015019    .0012839
     cand_exp_teach |  -.0112972   .0111942    -1.01   0.313    -.0332557    .0106614
   cand_exp_council |   .0048714    .011252     0.43   0.665    -.0172005    .0269433
    cand_exp_lawyer |  -.0102383   .0117674    -0.87   0.384    -.0333214    .0128448
  cand_exp_business |  -.0095326   .0112929    -0.84   0.399    -.0316847    .0126195
           zero_exp |          0  (omitted)
     cand_biden_p59 |   .0077247   .0116267     0.66   0.507    -.0150823    .0305317
     cand_biden_p57 |   .0024953   .0113039     0.22   0.825    -.0196786    .0246692
     cand_biden_p55 |    .020742   .0116792     1.78   0.076     -.002168     .043652
     cand_biden_p53 |   .0124567   .0113656     1.10   0.273    -.0098381    .0347514
         zero_biden |          0  (omitted)
         cand_dist1 |   .0476531   .0145354     3.28   0.001     .0191404    .0761658
         cand_dist2 |   .0753717   .0149865     5.03   0.000     .0459741    .1047693
         cand_dist3 |   .0842905    .015919     5.29   0.000     .0530637    .1155174
         cand_dist4 |   .0294024   .0144037     2.04   0.041     .0011479    .0576568
         cand_dist5 |   .0074005   .0149824     0.49   0.621    -.0219891    .0367901
         cand_dist6 |   .0191165   .0143248     1.33   0.182    -.0089831    .0472161
          zero_dist |          0  (omitted)
 cand_policy_abort1 |   .0159245    .013649     1.17   0.244    -.0108494    .0426984
 cand_policy_abort2 |   .0055988    .013015     0.43   0.667    -.0199315    .0311292
   cand_policy_tax1 |   .0261939   .0133741     1.96   0.050    -.0000408    .0524286
   cand_policy_tax2 |   .0195506   .0132069     1.48   0.139    -.0063561    .0454573
cand_policy_health1 |   .0168457   .0133616     1.26   0.208    -.0093645     .043056
cand_policy_health2 |   .0248465   .0133922     1.86   0.064    -.0014238    .0511167
   cand_policy_eco1 |   .0227985   .0121631     1.87   0.061    -.0010608    .0466577
           zero_eco |          0  (omitted)
    cand_policy_aa1 |   .0550258   .0128767     4.27   0.000     .0297668    .0802847
    cand_policy_aa2 |   .0469467   .0123962     3.79   0.000     .0226301    .0712632
    cand_policy_aa3 |  -.0674685   .0120448    -5.60   0.000    -.0910956   -.0438414
       zero_racepol |          0  (omitted)
              _cons |  -.0816818   .0426365    -1.92   0.056    -.1653179    .0019542
-------------------------------------------------------------------------------------

.                 eststo pool_fair

.                 loc b_pool_fair = string(round(_b[_cons], 0.001), "%9.3f")

.         
.                 reg favor_black `reg_race' `reg_sex' cand_age `reg_exp' `reg_biden' `reg_distpop' `reg_i
> ssues' `reg_affirm', vce(cluster r_id)
note: zero_race omitted because of collinearity.
note: zero_sex omitted because of collinearity.
note: zero_exp omitted because of collinearity.
note: zero_biden omitted because of collinearity.
note: zero_dist omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: zero_racepol omitted because of collinearity.

Linear regression                               Number of obs     =      7,235
                                                F(29, 1446)       =      12.33
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0473
                                                Root MSE          =     .47274

                                      (Std. err. adjusted for 1,447 clusters in r_id)
-------------------------------------------------------------------------------------
                    |               Robust
        favor_black | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
         cand_black |   .2085015   .0141547    14.73   0.000     .1807356    .2362674
          zero_race |          0  (omitted)
         cand_asian |   .0677749   .0131358     5.16   0.000     .0420075    .0935422
         cand_hispa |   .0547881   .0139317     3.93   0.000     .0274597    .0821166
        cand_female |   .0049428   .0097293     0.51   0.612    -.0141423    .0240278
           zero_sex |          0  (omitted)
           cand_age |   .0006283   .0009236     0.68   0.496    -.0011834      .00244
     cand_exp_teach |  -.0202997   .0150288    -1.35   0.177    -.0497802    .0091809
   cand_exp_council |   .0079631   .0150901     0.53   0.598    -.0216376    .0375639
    cand_exp_lawyer |  -.0087487   .0153167    -0.57   0.568     -.038794    .0212965
  cand_exp_business |   -.004368   .0151143    -0.29   0.773    -.0340164    .0252803
           zero_exp |          0  (omitted)
     cand_biden_p59 |  -.0007645   .0149156    -0.05   0.959    -.0300231    .0284941
     cand_biden_p57 |   .0037048   .0149604     0.25   0.804    -.0256415    .0330511
     cand_biden_p55 |    .009011   .0153878     0.59   0.558    -.0211738    .0391959
     cand_biden_p53 |   .0037315   .0148936     0.25   0.802    -.0254839     .032947
         zero_biden |          0  (omitted)
         cand_dist1 |  -.0081226    .018972    -0.43   0.669    -.0453382    .0290929
         cand_dist2 |   .0595374   .0192734     3.09   0.002     .0217306    .0973443
         cand_dist3 |   .0815819   .0196898     4.14   0.000     .0429583    .1202055
         cand_dist4 |   .0040867   .0181139     0.23   0.822    -.0314457    .0396191
         cand_dist5 |    .010553    .018321     0.58   0.565    -.0253855    .0464916
         cand_dist6 |   .0127627   .0180556     0.71   0.480    -.0226552    .0481807
          zero_dist |          0  (omitted)
 cand_policy_abort1 |   .0177652   .0174459     1.02   0.309    -.0164568    .0519872
 cand_policy_abort2 |  -.0197158   .0172713    -1.14   0.254    -.0535953    .0141637
   cand_policy_tax1 |  -.0017138    .018355    -0.09   0.926    -.0377191    .0342916
   cand_policy_tax2 |  -.0006839   .0175229    -0.04   0.969     -.035057    .0336892
cand_policy_health1 |  -.0036646   .0172203    -0.21   0.832     -.037444    .0301148
cand_policy_health2 |   .0115475   .0171678     0.67   0.501     -.022129    .0452239
   cand_policy_eco1 |   .0062564   .0154166     0.41   0.685     -.023985    .0364977
           zero_eco |          0  (omitted)
    cand_policy_aa1 |   .0788088    .016211     4.86   0.000     .0470091    .1106084
    cand_policy_aa2 |   .0642001   .0163436     3.93   0.000     .0321403    .0962599
    cand_policy_aa3 |   -.050716   .0153184    -3.31   0.001    -.0807647   -.0206672
       zero_racepol |          0  (omitted)
              _cons |   .2037039   .0549341     3.71   0.000     .0959448    .3114631
-------------------------------------------------------------------------------------

.                 eststo pool_favorb

.                 loc b_pool_favorb = string(round(_b[_cons], 0.001), "%9.3f")

.                 
.                 reg favor_white `reg_race' `reg_sex' cand_age `reg_exp' `reg_biden' `reg_distpop' `reg_i
> ssues' `reg_affirm', vce(cluster r_id)
note: zero_race omitted because of collinearity.
note: zero_sex omitted because of collinearity.
note: zero_exp omitted because of collinearity.
note: zero_biden omitted because of collinearity.
note: zero_dist omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: zero_racepol omitted because of collinearity.

Linear regression                               Number of obs     =      7,235
                                                F(29, 1446)       =       8.45
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0373
                                                Root MSE          =     .39461

                                      (Std. err. adjusted for 1,447 clusters in r_id)
-------------------------------------------------------------------------------------
                    |               Robust
        favor_white | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
         cand_black |  -.1434882   .0123146   -11.65   0.000    -.1676446   -.1193318
          zero_race |          0  (omitted)
         cand_asian |  -.0943978   .0124966    -7.55   0.000    -.1189112   -.0698844
         cand_hispa |  -.1079968   .0126796    -8.52   0.000    -.1328692   -.0831244
        cand_female |  -.0158432   .0083537    -1.90   0.058    -.0322298    .0005434
           zero_sex |          0  (omitted)
           cand_age |   -.000148   .0007553    -0.20   0.845    -.0016295    .0013335
     cand_exp_teach |   .0152797   .0129572     1.18   0.238    -.0101372    .0406965
   cand_exp_council |   .0064776   .0127683     0.51   0.612    -.0185688     .031524
    cand_exp_lawyer |   .0088431    .013338     0.66   0.507    -.0173208    .0350071
  cand_exp_business |   .0088478   .0128516     0.69   0.491     -.016362    .0340575
           zero_exp |          0  (omitted)
     cand_biden_p59 |   .0072319    .013357     0.54   0.588    -.0189693     .033433
     cand_biden_p57 |   .0129015    .012773     1.01   0.313     -.012154    .0379571
     cand_biden_p55 |   .0005938    .013108     0.05   0.964    -.0251188    .0263065
     cand_biden_p53 |   .0048605   .0130949     0.37   0.711    -.0208266    .0305475
         zero_biden |          0  (omitted)
         cand_dist1 |  -.0880775   .0162578    -5.42   0.000    -.1199689   -.0561861
         cand_dist2 |  -.0959153   .0163861    -5.85   0.000    -.1280585   -.0637722
         cand_dist3 |  -.0980727   .0165465    -5.93   0.000    -.1305304   -.0656149
         cand_dist4 |  -.0352711   .0160096    -2.20   0.028    -.0666756   -.0038666
         cand_dist5 |  -.0157354   .0165591    -0.95   0.342    -.0482177    .0167469
         cand_dist6 |  -.0226217   .0160661    -1.41   0.159     -.054137    .0088936
          zero_dist |          0  (omitted)
 cand_policy_abort1 |   .0277286   .0146102     1.90   0.058    -.0009309     .056388
 cand_policy_abort2 |  -.0013596   .0145265    -0.09   0.925    -.0298549    .0271357
   cand_policy_tax1 |  -.0063142   .0144584    -0.44   0.662    -.0346759    .0220475
   cand_policy_tax2 |  -.0000633   .0146613    -0.00   0.997     -.028823    .0286964
cand_policy_health1 |   .0113191   .0146406     0.77   0.440    -.0174001    .0400382
cand_policy_health2 |  -.0010264   .0146812    -0.07   0.944    -.0298251    .0277723
   cand_policy_eco1 |  -.0071555   .0130724    -0.55   0.584    -.0327984    .0184875
           zero_eco |          0  (omitted)
    cand_policy_aa1 |  -.0016435   .0129328    -0.13   0.899    -.0270125    .0237256
    cand_policy_aa2 |  -.0109724   .0123969    -0.89   0.376    -.0352903    .0133455
    cand_policy_aa3 |   .0683973   .0137672     4.97   0.000     .0413914    .0954032
       zero_racepol |          0  (omitted)
              _cons |   .3193532   .0473998     6.74   0.000     .2263735     .412333
-------------------------------------------------------------------------------------

.                 eststo pool_favorw

.                 loc b_pool_favorw = string(round(_b[_cons], 0.001), "%9.3f")

.                 
.                 coefplot (pool_fair, label() mc(gs4) ciopts(color(gs4) lw(med))) ///
>                                         , bylabel("{bf:(a) Black over White, Differ.}") || ///
>                                 (pool_favorb, label() mc(gs4) ciopts(color(gs4) lw(med))) ///
>                                         , bylabel("{bf:(b) Black over White, Binary}") || ///   
>                                  (pool_favorw, label() mc(gs4) ciopts(color(gs4) lw(med))) ///
>                                         , bylabel("{bf:(c) White over Black, Binary}") ///
>                                 || , drop(_cons cand_age) omitted baselevels ms(c) msize(medsmall) ///
>                                 ylabel(,labsize(vsmall)) ///
>                         xline(0, lc(black)) nokey ///
>                         subtitle(, bcolor(white) color(black) size(vsmall)) ///
>                         byopts(row(1) note("`notes'", size(vsmall)) t1title("{bf:`title'}", size(small))
> ) ///
>                         xtitle("Effects of Candidate Attributes (Scale 0 to 1)", size(vsmall)) ///
>                         xlabel(-0.2(0.1)0.2,labsize(small)) norecycle ///
>                         headings(cand_black = "{bf: Race}" ///
>                                         cand_female = "{bf: Gender}" ///
>                                         cand_exp_teach = "{bf: Occupation}" ///
>                                         cand_biden_p59 = "{bf: District Vote for Biden}" ///
>                                         cand_dist1 = "{bf: District Racial % [W,B,A,H,O]}" ///
>                                         cand_policy_abort1 = "{bf: Abortion}" ///
>                                         cand_policy_tax1 = "{bf: Tax Policy}" ///
>                                         cand_policy_health1 = "{bf: Healthcare}" ///
>                                         cand_policy_eco1 = "{bf: Energy}" ///
>                                         cand_policy_aa1 = "{bf: Affirmative Action}" ///
>                                         , labsize(vsmall)) 
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)

.         
.                 addplot 1: ,note("Mean, Baseline Categories = `b_pool_fair'", size(vsmall)) norescaling

.                 addplot 2: ,note("Mean, Baseline Categories = `b_pool_favorb'", size(vsmall)) norescalin
> g

.                 addplot 3: ,note("Mean, Baseline Categories = `b_pool_favorw'", size(vsmall)) norescalin
> g

.                 
.                 graph display, xsize(5) ysize(3.7) margins(vsmall)      

.                 // Pooled outcomes (not in paper)
.                 
.         // Effect of candidate attributes on main outcomes, interacted
.                 // Interacted
.                 reg out_fair_bwdiff `reg_sex' cand_age `reg_exp' `reg_biden' `reg_distpop' `reg_issues' 
> `int' cand_age , vce(cluster r_id)
note: zero_sex omitted because of collinearity.
note: zero_exp omitted because of collinearity.
note: zero_biden omitted because of collinearity.
note: zero_dist omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.
note: cand_age omitted because of collinearity.

Linear regression                               Number of obs     =      7,233
                                                F(38, 1446)       =      10.79
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0662
                                                Root MSE          =     .37231

                                      (Std. err. adjusted for 1,447 clusters in r_id)
-------------------------------------------------------------------------------------
                    |               Robust
    out_fair_bwdiff | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |   .0139265   .0076268     1.83   0.068    -.0010342    .0288872
           zero_sex |          0  (omitted)
           cand_age |  -.0000902   .0007096    -0.13   0.899    -.0014822    .0013017
     cand_exp_teach |  -.0112882   .0112302    -1.01   0.315    -.0333175     .010741
   cand_exp_council |   .0049001   .0112728     0.43   0.664    -.0172127     .027013
    cand_exp_lawyer |   -.010402   .0117992    -0.88   0.378    -.0335474    .0127434
  cand_exp_business |  -.0089442   .0113374    -0.79   0.430    -.0311838    .0132954
           zero_exp |          0  (omitted)
     cand_biden_p59 |   .0079005   .0116374     0.68   0.497    -.0149274    .0307284
     cand_biden_p57 |    .002314   .0112995     0.20   0.838    -.0198512    .0244792
     cand_biden_p55 |    .020527   .0117194     1.75   0.080    -.0024619    .0435159
     cand_biden_p53 |   .0122306   .0114134     1.07   0.284    -.0101581    .0346192
         zero_biden |          0  (omitted)
         cand_dist1 |   .0470683   .0146007     3.22   0.001     .0184276    .0757091
         cand_dist2 |   .0742289   .0150229     4.94   0.000     .0447599     .103698
         cand_dist3 |    .084251   .0159216     5.29   0.000     .0530191    .1154828
         cand_dist4 |   .0287881   .0144329     1.99   0.046     .0004764    .0570997
         cand_dist5 |   .0064837   .0150236     0.43   0.666    -.0229867    .0359542
         cand_dist6 |   .0183777   .0143633     1.28   0.201    -.0097974    .0465528
          zero_dist |          0  (omitted)
 cand_policy_abort1 |    .015618   .0136396     1.15   0.252    -.0111375    .0423735
 cand_policy_abort2 |   .0051392   .0130142     0.39   0.693    -.0203895     .030668
   cand_policy_tax1 |   .0252993   .0134408     1.88   0.060    -.0010662    .0516647
   cand_policy_tax2 |   .0194576   .0132096     1.47   0.141    -.0064544    .0453697
cand_policy_health1 |    .015918   .0133605     1.19   0.234    -.0102901    .0421262
cand_policy_health2 |   .0239248   .0133908     1.79   0.074    -.0023428    .0501923
   cand_policy_eco1 |   .0220292   .0121881     1.81   0.071     -.001879    .0459373
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          white_aa1 |   .0467187   .0229738     2.03   0.042     .0016532    .0917842
          white_aa2 |   .0410289   .0231961     1.77   0.077    -.0044727    .0865304
          white_aa3 |  -.1027482   .0221974    -4.63   0.000    -.1462908   -.0592056
          black_aa0 |   .1868773    .022748     8.22   0.000     .1422546       .2315
          black_aa1 |   .2470242   .0230655    10.71   0.000     .2017789    .2922696
          black_aa2 |   .2276338   .0230118     9.89   0.000     .1824938    .2727738
          black_aa3 |   .1179799   .0222085     5.31   0.000     .0744156    .1615442
          asian_aa0 |   .0384585   .0216096     1.78   0.075     -.003931     .080848
          asian_aa1 |    .095862   .0233697     4.10   0.000     .0500199    .1417041
          asian_aa2 |   .1096244   .0230638     4.75   0.000     .0643822    .1548665
          asian_aa3 |   .0160585   .0221627     0.72   0.469    -.0274159     .059533
          hispa_aa0 |   .0634578   .0200615     3.16   0.002     .0241051    .1028104
          hispa_aa1 |   .1206673   .0236912     5.09   0.000     .0741945    .1671401
          hispa_aa2 |   .1046724   .0233395     4.48   0.000     .0588895    .1504552
          hispa_aa3 |    .004609   .0228092     0.20   0.840    -.0401336    .0493517
           cand_age |          0  (omitted)
              _cons |   -.068754   .0444104    -1.55   0.122    -.1558697    .0183617
-------------------------------------------------------------------------------------

.                 eststo fair_bwdiff

.                 loc b_fair = string(round(_b[_cons], 0.001), "%9.3f")

.                 
.                 reg favor_black `reg_sex' cand_age `reg_exp' `reg_biden' `reg_distpop' `reg_issues' `int
> ' cand_age , vce(cluster r_id)
note: zero_sex omitted because of collinearity.
note: zero_exp omitted because of collinearity.
note: zero_biden omitted because of collinearity.
note: zero_dist omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.
note: cand_age omitted because of collinearity.

Linear regression                               Number of obs     =      7,235
                                                F(38, 1446)       =       9.48
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0479
                                                Root MSE          =     .47287

                                      (Std. err. adjusted for 1,447 clusters in r_id)
-------------------------------------------------------------------------------------
                    |               Robust
        favor_black | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |    .005151   .0097603     0.53   0.598    -.0139948    .0242968
           zero_sex |          0  (omitted)
           cand_age |   .0006495   .0009238     0.70   0.482    -.0011627    .0024618
     cand_exp_teach |  -.0207091    .015054    -1.38   0.169    -.0502392    .0088209
   cand_exp_council |   .0078728   .0150862     0.52   0.602    -.0217203    .0374659
    cand_exp_lawyer |  -.0087354   .0153553    -0.57   0.570    -.0388565    .0213857
  cand_exp_business |  -.0040933   .0151425    -0.27   0.787     -.033797    .0256104
           zero_exp |          0  (omitted)
     cand_biden_p59 |   -.000621   .0149614    -0.04   0.967    -.0299694    .0287275
     cand_biden_p57 |   .0028445   .0149619     0.19   0.849    -.0265049    .0321938
     cand_biden_p55 |   .0091205   .0154242     0.59   0.554    -.0211357    .0393766
     cand_biden_p53 |   .0031505   .0149398     0.21   0.833    -.0261555    .0324564
         zero_biden |          0  (omitted)
         cand_dist1 |  -.0086445   .0190198    -0.45   0.650    -.0459538    .0286649
         cand_dist2 |   .0587682   .0193013     3.04   0.002     .0209066    .0966298
         cand_dist3 |    .081679   .0196924     4.15   0.000     .0430503    .1203077
         cand_dist4 |   .0037114   .0180969     0.21   0.838    -.0317875    .0392104
         cand_dist5 |   .0101461   .0183303     0.55   0.580    -.0258108     .046103
         cand_dist6 |     .01192   .0180836     0.66   0.510     -.023553    .0473929
          zero_dist |          0  (omitted)
 cand_policy_abort1 |   .0178348   .0174384     1.02   0.307    -.0163724     .052042
 cand_policy_abort2 |  -.0201615   .0172396    -1.17   0.242    -.0539788    .0136558
   cand_policy_tax1 |  -.0016382   .0184155    -0.09   0.929    -.0377622    .0344858
   cand_policy_tax2 |  -.0006893   .0175509    -0.04   0.969    -.0351173    .0337388
cand_policy_health1 |  -.0040932   .0172313    -0.24   0.812    -.0378941    .0297077
cand_policy_health2 |   .0114882    .017196     0.67   0.504    -.0222435    .0452199
   cand_policy_eco1 |   .0057014   .0153933     0.37   0.711    -.0244941    .0358968
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          white_aa1 |   .0674027    .027542     2.45   0.015     .0133762    .1214292
          white_aa2 |   .0587221   .0280951     2.09   0.037     .0036107    .1138335
          white_aa3 |  -.0518112   .0256577    -2.02   0.044    -.1021416   -.0014809
          black_aa0 |   .2172056   .0283552     7.66   0.000     .1615839    .2728273
          black_aa1 |   .2906073   .0281521    10.32   0.000      .235384    .3458305
          black_aa2 |    .267838   .0281557     9.51   0.000     .2126075    .3230684
          black_aa3 |   .1313504   .0280183     4.69   0.000     .0763895    .1863113
          asian_aa0 |   .0452776   .0293684     1.54   0.123    -.0123316    .1028867
          asian_aa1 |    .123444   .0306164     4.03   0.000     .0633868    .1835013
          asian_aa2 |   .1410231   .0305396     4.62   0.000     .0811164    .2009298
          asian_aa3 |    .034984   .0291186     1.20   0.230    -.0221352    .0921033
          hispa_aa0 |   .0422659   .0292664     1.44   0.149    -.0151432     .099675
          hispa_aa1 |   .1449399   .0314273     4.61   0.000      .083292    .2065879
          hispa_aa2 |   .1022597   .0308682     3.31   0.001     .0417085     .162811
          hispa_aa3 |   .0035256   .0287649     0.12   0.902    -.0528999    .0599511
           cand_age |          0  (omitted)
              _cons |   .2080311   .0563604     3.69   0.000     .0974741     .318588
-------------------------------------------------------------------------------------

.                 eststo pool_favorb

.                 loc b_pool_favorb = string(round(_b[_cons], 0.001), "%9.3f")

.         
.                 reg favor_white `reg_sex' cand_age `reg_exp' `reg_biden' `reg_distpop' `reg_issues' `int
> ' cand_age , vce(cluster r_id)
note: zero_sex omitted because of collinearity.
note: zero_exp omitted because of collinearity.
note: zero_biden omitted because of collinearity.
note: zero_dist omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.
note: cand_age omitted because of collinearity.

Linear regression                               Number of obs     =      7,235
                                                F(38, 1446)       =       6.60
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0390
                                                Root MSE          =      .3945

                                      (Std. err. adjusted for 1,447 clusters in r_id)
-------------------------------------------------------------------------------------
                    |               Robust
        favor_white | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |  -.0150903   .0083654    -1.80   0.071    -.0314999    .0013193
           zero_sex |          0  (omitted)
           cand_age |  -.0001596   .0007549    -0.21   0.833    -.0016404    .0013211
     cand_exp_teach |   .0148375   .0129705     1.14   0.253    -.0106056    .0402805
   cand_exp_council |   .0061485   .0127962     0.48   0.631    -.0189526    .0312497
    cand_exp_lawyer |   .0093238   .0133387     0.70   0.485    -.0168415    .0354891
  cand_exp_business |   .0088621   .0128599     0.69   0.491    -.0163639    .0340882
           zero_exp |          0  (omitted)
     cand_biden_p59 |    .006791    .013358     0.51   0.611    -.0194122    .0329942
     cand_biden_p57 |   .0121978    .012792     0.95   0.340    -.0128951    .0372906
     cand_biden_p55 |   .0005204   .0131081     0.04   0.968    -.0251925    .0262334
     cand_biden_p53 |   .0046596   .0131083     0.36   0.722    -.0210538     .030373
         zero_biden |          0  (omitted)
         cand_dist1 |    -.08814   .0162847    -5.41   0.000     -.120084   -.0561959
         cand_dist2 |   -.095249   .0163749    -5.82   0.000    -.1273702   -.0631278
         cand_dist3 |  -.0979933   .0165669    -5.92   0.000     -.130491   -.0654956
         cand_dist4 |  -.0347584   .0160192    -2.17   0.030    -.0661816   -.0033351
         cand_dist5 |  -.0151841   .0165637    -0.92   0.359    -.0476755    .0173074
         cand_dist6 |  -.0232337   .0160747    -1.45   0.149    -.0547659    .0082984
          zero_dist |          0  (omitted)
 cand_policy_abort1 |   .0282567   .0146173     1.93   0.053    -.0004167    .0569301
 cand_policy_abort2 |  -.0013828   .0145531    -0.10   0.924    -.0299304    .0271647
   cand_policy_tax1 |  -.0045702    .014486    -0.32   0.752     -.032986    .0238456
   cand_policy_tax2 |   .0000771   .0146774     0.01   0.996    -.0287142    .0288684
cand_policy_health1 |   .0118419   .0146366     0.81   0.419    -.0168693    .0405531
cand_policy_health2 |  -.0000755   .0147089    -0.01   0.996    -.0289285    .0287774
   cand_policy_eco1 |  -.0066636   .0131077    -0.51   0.611    -.0323757    .0190485
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          white_aa1 |   .0000956    .026995     0.00   0.997    -.0528579    .0530491
          white_aa2 |  -.0238993     .02628    -0.91   0.363    -.0754504    .0276517
          white_aa3 |   .1002005   .0277142     3.62   0.000     .0458361    .1545649
          black_aa0 |  -.1206746   .0245328    -4.92   0.000    -.1687983    -.072551
          black_aa1 |  -.1375454   .0236912    -5.81   0.000    -.1840181   -.0910727
          black_aa2 |  -.1328895   .0234628    -5.66   0.000    -.1789142   -.0868648
          black_aa3 |  -.1086454   .0244693    -4.44   0.000    -.1566446   -.0606462
          asian_aa0 |  -.0826753   .0271491    -3.05   0.002     -.135931   -.0294195
          asian_aa1 |   -.091899   .0267097    -3.44   0.001    -.1442929   -.0395051
          asian_aa2 |  -.1063006   .0268404    -3.96   0.000    -.1589508   -.0536504
          asian_aa3 |  -.0210749   .0282858    -0.75   0.456    -.0765605    .0344106
          hispa_aa0 |  -.1268299   .0257053    -4.93   0.000    -.1772537   -.0764062
          hispa_aa1 |  -.1034262   .0263798    -3.92   0.000    -.1551729   -.0516794
          hispa_aa2 |  -.1061496   .0262152    -4.05   0.000    -.1575735   -.0547258
          hispa_aa3 |  -.0174129   .0292755    -0.59   0.552      -.07484    .0400141
           cand_age |          0  (omitted)
              _cons |   .3137008   .0494773     6.34   0.000     .2166458    .4107558
-------------------------------------------------------------------------------------

.                 eststo pool_favorw

.                 loc b_pool_favorw = string(round(_b[_cons], 0.001), "%9.3f")

.         
.                 coefplot (fair_bwdiff, label() mc(gs4) ciopts(color(gs4) lw(med))) ///
>                                         , bylabel("{bf:(a) Black over White, Differ.}") || ///
>                                 (pool_favorb, label() mc(gs4) ciopts(color(gs4) lw(med))) ///
>                                         , bylabel("{bf:(b) Black over White, Binary}") || ///           
>                                  (pool_favorw, label() mc(gs4) ciopts(color(gs4) lw(med))) ///
>                                         , bylabel("{bf:(c) White over Black, Binary}") ///
>                                 || , drop(_cons `reg_sex' `reg_issues' cand_age `reg_exp' `reg_biden' `r
> eg_distpop') ///
>                                 omitted baselevels ms(c) msize(med) ///
>                                 ylabel(,labsize(vsmall)) ///
>                         xline(0, lc(black)) nokey ///
>                         subtitle(, bcolor(white) color(black) size(vsmall)) ///
>                         byopts(row(1) t1title("{bf:`title'}", size(small))) ///
>                         xtitle("Effects of Candidate Attributes (Scale 0 to 1)", size(vsmall)) ///
>                         xlabel(-0.2(0.1)0.2,labsize(small)) norecycle ///
>                         headings(white_aa0 = "{bf: White X Affirmative Action}" ///
>                                         black_aa0 = "{bf: Black X Affirmative Action}" ///
>                                         asian_aa0 = "{bf: Asian X Affirmative Action}" ///
>                                         hispa_aa0 = "{bf: Hispanic X Affirmative Action}" ///
>                                         , labsize(vsmall)) 
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)

. 
.                 addplot 1: ,note("Mean, Baseline Categories = `b_fair'", size(vsmall)) norescaling

.                 addplot 2: ,note("Mean, Baseline Categories = `b_pool_favorb'", size(vsmall)) norescalin
> g

.                 addplot 3: ,note("Mean, Baseline Categories = `b_pool_favorw'", size(vsmall)) norescalin
> g

.                 
.         
.                 graph display, xsize(4.5) ysize(3.4) margins(vsmall)

.                 
.                 graph export figure_s2.png, as(png) replace
(file figure_s2.png not found)
file figure_s2.png saved as PNG format

.         
. 
end of do-file

. do 8_appendix_figure_s3.do

. /*
>         Figure S3. Vote Outcome in Study 2
> */
. 
. use data_study_2.dta, clear

. 
. 
. // Set omitted categories
.         gen zero_race = 0

.         label var zero_race "White"

.         gen zero_sex = 0

.         label var zero_sex "Male"

.         gen zero_eco = 0

.         label var zero_eco "Maintain investment in energy"

.         gen zero_biden = 0

.         label var zero_biden "Vote Share: 51%"

.         gen zero_exp = 0

.         label var zero_exp "Political newcomer"

.         gen zero_dist = 0

.         label var zero_dist "[63, 8, 13, 11, 5]"

.         gen zero_racepol = 0

.         label var zero_racepol "Not shown policy"

.         
. // Set regression variables
.         loc reg_race "cand_black zero_race cand_asian cand_hispa"

.         loc reg_sex "cand_female zero_sex"

.         loc reg_exp "cand_exp_teach cand_exp_council cand_exp_lawyer cand_exp_business zero_exp"

.         loc reg_biden "cand_biden_p59 cand_biden_p57 cand_biden_p55 cand_biden_p53 zero_biden"

.         loc reg_distpop "cand_dist1 cand_dist2 cand_dist3 cand_dist4 cand_dist5 cand_dist6 zero_dist"

.         loc reg_issues "cand_policy_abort1 cand_policy_abort2 cand_policy_tax1 cand_policy_tax2"

.         loc reg_issues "`reg_issues' cand_policy_health1 cand_policy_health2 cand_policy_eco1 zero_eco"

.         loc reg_affirm "cand_policy_aa1 cand_policy_aa2 cand_policy_aa3 zero_racepol"

.         loc reg_affirm2 "noracepolicy cand_policy_aa1 cand_policy_aa2 cand_policy_aa3 "

.         
. // Interactive Terms for Black Candidate X Affirmative Action
.         gen noracepolicy = cand_policy_aa1 == 0 & cand_policy_aa2 == 0 & cand_policy_aa3 == 0   

.         
.         loc int ""

.         foreach r in white black asian hispa {
  2.                 gen `r'_aa1 = cand_policy_aa1*cand_`r'
  3.                 gen `r'_aa2 = cand_policy_aa2*cand_`r'
  4.                 gen `r'_aa3 = cand_policy_aa3*cand_`r'
  5.                 gen `r'_aa0 = noracepolicy*cand_`r'
  6.                 
.                 loc lab = proper("`r'")
  7.                 if "`lab'" == "Hispa" loc lab = "Hispanic"
  8.         
.                 label var `r'_aa0 "`lab' X No Position"
  9.                 label var `r'_aa1 "`lab' X Expand"
 10.                 label var `r'_aa2 "`lab' X Keep"
 11.                 label var `r'_aa3 "`lab' X End"
 12.                 
.                 loc int "`int' `r'_aa0 `r'_aa1 `r'_aa2 `r'_aa3"
 13.         
.         }

.         // set reference
.         replace white_aa0 = 0
(560 real changes made)

.         label var noracepolicy "Not shown position"

.         
.         gen out_fair_bwdiff = out_fair_black - out_fair_white
(2 missing values generated)

.                 
. //============================================================================== Regress the things
. 
.                 eststo clear

.                 reg out_vote `reg_distpop' `reg_race' `reg_affirm' `reg_issues' `reg_sex' cand_age `reg_
> exp' `reg_biden' , vce(cluster r_id)
note: zero_dist omitted because of collinearity.
note: zero_race omitted because of collinearity.
note: zero_racepol omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: zero_sex omitted because of collinearity.
note: zero_exp omitted because of collinearity.
note: zero_biden omitted because of collinearity.

Linear regression                               Number of obs     =      7,224
                                                F(29, 1446)       =       2.92
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0109
                                                Root MSE          =     .32853

                                      (Std. err. adjusted for 1,447 clusters in r_id)
-------------------------------------------------------------------------------------
                    |               Robust
           out_vote | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
         cand_dist1 |   .0114438    .011504     0.99   0.320    -.0111225    .0340101
         cand_dist2 |   .0164149   .0117674     1.39   0.163    -.0066681    .0394979
         cand_dist3 |   .0292465   .0114667     2.55   0.011     .0067533    .0517396
         cand_dist4 |   .0122431   .0112371     1.09   0.276    -.0097996    .0342858
         cand_dist5 |   .0018865   .0113478     0.17   0.868    -.0203734    .0241463
         cand_dist6 |   .0042554   .0113102     0.38   0.707    -.0179309    .0264416
          zero_dist |          0  (omitted)
         cand_black |   .0073133   .0080002     0.91   0.361      -.00838    .0230066
          zero_race |          0  (omitted)
         cand_asian |  -.0146447   .0078926    -1.86   0.064    -.0301269    .0008375
         cand_hispa |   .0059401   .0079643     0.75   0.456    -.0096827    .0215628
    cand_policy_aa1 |   .0051758   .0110523     0.47   0.640    -.0165044     .026856
    cand_policy_aa2 |   .0001029   .0116255     0.01   0.993    -.0227018    .0229077
    cand_policy_aa3 |  -.0000724   .0114817    -0.01   0.995    -.0225951    .0224502
       zero_racepol |          0  (omitted)
 cand_policy_abort1 |  -.0688173   .0129692    -5.31   0.000    -.0942577   -.0433769
 cand_policy_abort2 |  -.0051001   .0123613    -0.41   0.680    -.0293481    .0191479
   cand_policy_tax1 |   .0044148    .012849     0.34   0.731    -.0207899    .0296195
   cand_policy_tax2 |   .0040482   .0123151     0.33   0.742    -.0201092    .0282057
cand_policy_health1 |  -.0054447   .0122107    -0.45   0.656    -.0293972    .0185078
cand_policy_health2 |   .0141387   .0118857     1.19   0.234    -.0091763    .0374537
   cand_policy_eco1 |   .0074622   .0104457     0.71   0.475    -.0130281    .0279526
           zero_eco |          0  (omitted)
        cand_female |   .0058582   .0057862     1.01   0.311     -.005492    .0172084
           zero_sex |          0  (omitted)
           cand_age |   .0011606   .0006246     1.86   0.063    -.0000645    .0023858
     cand_exp_teach |  -.0020548   .0082417    -0.25   0.803    -.0182218    .0141123
   cand_exp_council |   .0061273   .0080776     0.76   0.448    -.0097178    .0219724
    cand_exp_lawyer |  -.0002228   .0085703    -0.03   0.979    -.0170344    .0165889
  cand_exp_business |  -.0047286   .0081454    -0.58   0.562    -.0207067    .0112495
           zero_exp |          0  (omitted)
     cand_biden_p59 |   -.000046   .0081146    -0.01   0.995    -.0159636    .0158716
     cand_biden_p57 |  -.0038032    .008207    -0.46   0.643    -.0199021    .0122957
     cand_biden_p55 |  -.0001193   .0084174    -0.01   0.989    -.0166309    .0163923
     cand_biden_p53 |   .0006084   .0081494     0.07   0.941    -.0153776    .0165943
         zero_biden |          0  (omitted)
              _cons |   .3943586   .0385768    10.22   0.000     .3186862     .470031
-------------------------------------------------------------------------------------

.                 eststo pool_vote

.                 loc b_pool_vote = string(round(_b[_cons], 0.001), "%9.3f")

.                 
.                 reg out_vote `reg_sex' `reg_exp' `reg_biden' `reg_distpop' `reg_issues' `int' cand_age, 
> vce(cluster r_id)       
note: zero_sex omitted because of collinearity.
note: zero_exp omitted because of collinearity.
note: zero_biden omitted because of collinearity.
note: zero_dist omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      7,224
                                                F(38, 1446)       =       2.40
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0114
                                                Root MSE          =     .32864

                                      (Std. err. adjusted for 1,447 clusters in r_id)
-------------------------------------------------------------------------------------
                    |               Robust
           out_vote | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |   .0057137   .0057959     0.99   0.324    -.0056556    .0170831
           zero_sex |          0  (omitted)
     cand_exp_teach |  -.0020345    .008255    -0.25   0.805    -.0182275    .0141584
   cand_exp_council |   .0060306    .008107     0.74   0.457    -.0098721    .0219333
    cand_exp_lawyer |  -.0001616   .0085952    -0.02   0.985    -.0170219    .0166987
  cand_exp_business |   -.004852   .0081584    -0.59   0.552    -.0208556    .0111517
           zero_exp |          0  (omitted)
     cand_biden_p59 |  -.0002863   .0081263    -0.04   0.972     -.016227    .0156543
     cand_biden_p57 |  -.0036412   .0082305    -0.44   0.658    -.0197862    .0125038
     cand_biden_p55 |  -.0004449   .0084433    -0.05   0.958    -.0170073    .0161174
     cand_biden_p53 |   .0006981   .0081691     0.09   0.932    -.0153266    .0167227
         zero_biden |          0  (omitted)
         cand_dist1 |   .0113366   .0115002     0.99   0.324    -.0112222    .0338954
         cand_dist2 |   .0163372    .011802     1.38   0.166    -.0068137     .039488
         cand_dist3 |   .0291251   .0114735     2.54   0.011     .0066186    .0516315
         cand_dist4 |   .0127287   .0112192     1.13   0.257     -.009279    .0347364
         cand_dist5 |   .0019869   .0113474     0.18   0.861    -.0202723     .024246
         cand_dist6 |   .0043543   .0113072     0.39   0.700     -.017826    .0265346
          zero_dist |          0  (omitted)
 cand_policy_abort1 |  -.0688938   .0129819    -5.31   0.000    -.0943593   -.0434284
 cand_policy_abort2 |  -.0051299   .0123655    -0.41   0.678     -.029386    .0191263
   cand_policy_tax1 |   .0044089   .0129161     0.34   0.733    -.0209273    .0297452
   cand_policy_tax2 |   .0038922   .0123416     0.32   0.753    -.0203171    .0281016
cand_policy_health1 |   -.005794   .0122435    -0.47   0.636    -.0298109    .0182229
cand_policy_health2 |   .0137502   .0118987     1.16   0.248    -.0095904    .0370908
   cand_policy_eco1 |   .0075184   .0104521     0.72   0.472    -.0129844    .0280212
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          white_aa1 |   .0156367   .0204122     0.77   0.444     -.024404    .0556773
          white_aa2 |  -.0035222   .0204204    -0.17   0.863    -.0435789    .0365344
          white_aa3 |  -.0085645   .0198769    -0.43   0.667    -.0475552    .0304263
          black_aa0 |   .0084431   .0192072     0.44   0.660    -.0292338      .04612
          black_aa1 |   .0089313   .0187386     0.48   0.634    -.0278265    .0456892
          black_aa2 |   .0038525   .0193446     0.20   0.842     -.034094     .041799
          black_aa3 |   .0124416   .0192542     0.65   0.518    -.0253275    .0502108
          asian_aa0 |  -.0181706   .0198466    -0.92   0.360    -.0571018    .0207605
          asian_aa1 |  -.0066882   .0212724    -0.31   0.753    -.0484163    .0350399
          asian_aa2 |  -.0248002   .0213433    -1.16   0.245    -.0666673    .0170668
          asian_aa3 |  -.0053797   .0212681    -0.25   0.800    -.0470994      .03634
          hispa_aa0 |   .0061081   .0202466     0.30   0.763    -.0336077    .0458239
          hispa_aa1 |   -.002823   .0206308    -0.14   0.891    -.0432925    .0376465
          hispa_aa2 |   .0267401   .0218813     1.22   0.222    -.0161824    .0696627
          hispa_aa3 |  -.0008743   .0209623    -0.04   0.967     -.041994    .0402454
           cand_age |   .0011391   .0006263     1.82   0.069    -.0000894    .0023677
              _cons |   .3961001    .040388     9.81   0.000     .3168747    .4753255
-------------------------------------------------------------------------------------

.                 eststo vote

.                 loc b_vote = string(round(_b[_cons], 0.001), "%9.3f")

.                 
.                 // All attributes, pooled 
.                 coefplot (pool_vote, label() mc(gs4) ciopts(color(gs4) lw(med))) ///
>                                         || , drop(_cons cand_age) omitted baselevels ms(c) msize(medsmal
> l) ///
>                                 ylabel(,labsize(vsmall)) ///
>                         xline(0, lc(black)) nokey ///
>                         subtitle("{bf:(a) Pooled Model}", bcolor(white) color(black) size(vsmall)) ///
>                         byopts(row(1) note("`notes'", size(vsmall)) t1title("{bf:`title'}", size(small))
> ) ///
>                         xtitle("Effects of Candidate Attributes (Scale 0 to 1)", size(vsmall)) ///
>                         xlabel(-0.2(0.1)0.2,labsize(small)) norecycle ///
>                         headings(cand_black = "{bf: Race}" ///
>                                         cand_female = "{bf: Gender}" ///
>                                         cand_exp_teach = "{bf: Occupation}" ///
>                                         cand_biden_p59 = "{bf: District Vote for Biden}" ///
>                                         cand_dist1 = "{bf: District Racial % [W,B,A,H,O]}" ///
>                                         cand_policy_abort1 = "{bf: Abortion}" ///
>                                         cand_policy_tax1 = "{bf: Tax Policy}" ///
>                                         cand_policy_health1 = "{bf: Healthcare}" ///
>                                         cand_policy_eco1 = "{bf: Energy}" ///
>                                         cand_policy_aa1 = "{bf: Affirmative Action}" ///
>                                         , labsize(vsmall)) note("Mean, Baseline Categories = `b_pool_vot
> e'", size(vsmall)) ///
>                                         saving(fig1.gph, replace)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(file fig1.gph not found)
file fig1.gph saved

.         
.                 // Effect of candidate attributes on main outcomes, interacted
.                 coefplot (vote, label() mc(gs4) ciopts(color(gs4) lw(med))) ///
>                                  || , drop(_cons `reg_sex' `reg_issues' cand_age `reg_exp' `reg_biden' `
> reg_distpop') ///
>                                 omitted baselevels ms(c) msize(med) ///
>                                 ylabel(,labsize(vsmall)) ///
>                         xline(0, lc(black)) nokey ///
>                         subtitle("{bf:(b) Interacted Model}", bcolor(white) color(black) size(vsmall)) /
> //
>                         byopts(row(1) t1title("{bf:`title'}", size(small))) ///
>                         xtitle("Effects of Candidate Attributes (Scale 0 to 1)", size(vsmall)) ///
>                         xlabel(-0.2(0.1)0.2,labsize(small)) norecycle ///
>                         headings(white_aa0 = "{bf: White X Affirmative Action}" ///
>                                         black_aa0 = "{bf: Black X Affirmative Action}" ///
>                                         asian_aa0 = "{bf: Asian X Affirmative Action}" ///
>                                         hispa_aa0 = "{bf: Hispanic X Affirmative Action}" ///
>                                         , labsize(vsmall)) note("Mean, Baseline Categories = `b_vote'", 
> size(vsmall)) ///
>                                         saving(fig2.gph, replace)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)
(file fig2.gph not found)
file fig2.gph saved

.                                         
.                 graph combine fig1.gph fig2.gph 
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class symbolsize, default attributes used)

. 
.                 graph display, xsize(4.5) ysize(3.4) margins(vsmall)    

.                 graph export figure_s3.png, as(png) replace
(file figure_s3.png not found)
file figure_s3.png saved as PNG format

.                 
. 
end of do-file

. do 9_appendix_figure_s4-s7.do

. /*
>         Figure S4 and S5: Pooled and Interacted Models by Race (Study 2)
>         
>         Figure S6 and S7: Pooled and Interacted Models by Party (Study 2)
> */
. 
. use data_study_2.dta, clear

. 
. // Set omitted categories
.         gen zero_race = 0

.         label var zero_race "White"

.         gen zero_sex = 0

.         label var zero_sex "Male"

.         gen zero_eco = 0

.         label var zero_eco "Maintain investment in energy"

.         gen zero_biden = 0

.         label var zero_biden "Vote Share: 51%"

.         gen zero_exp = 0

.         label var zero_exp "Political newcomer"

.         gen zero_dist = 0

.         label var zero_dist "[63, 8, 13, 11, 5]"

.         gen zero_racepol = 0

.         label var zero_racepol "Not shown policy"

.         
. // Set regression variables
.         loc reg_race "cand_black zero_race cand_asian cand_hispa"

.         loc reg_sex "cand_female zero_sex"

.         loc reg_exp "cand_exp_teach cand_exp_council cand_exp_lawyer cand_exp_business zero_exp"

.         loc reg_biden "cand_biden_p59 cand_biden_p57 cand_biden_p55 cand_biden_p53 zero_biden"

.         loc reg_distpop "cand_dist1 cand_dist2 cand_dist3 cand_dist4 cand_dist5 cand_dist6 zero_dist"

.         loc reg_issues "cand_policy_abort1 cand_policy_abort2 cand_policy_tax1 cand_policy_tax2"

.         loc reg_issues "`reg_issues' cand_policy_health1 cand_policy_health2 cand_policy_eco1 zero_eco"

.         loc reg_affirm "cand_policy_aa1 cand_policy_aa2 cand_policy_aa3 zero_racepol"

.         loc reg_affirm2 "noracepolicy cand_policy_aa1 cand_policy_aa2 cand_policy_aa3 "

.         
. // Interactive Terms for Black Candidate X Affirmative Action
.         gen noracepolicy = cand_policy_aa1 == 0 & cand_policy_aa2 == 0 & cand_policy_aa3 == 0   

.         
.         loc int ""

.         foreach r in white black asian hispa {
  2.                 gen `r'_aa1 = cand_policy_aa1*cand_`r'
  3.                 gen `r'_aa2 = cand_policy_aa2*cand_`r'
  4.                 gen `r'_aa3 = cand_policy_aa3*cand_`r'
  5.                 gen `r'_aa0 = noracepolicy*cand_`r'
  6.                 
.                 loc lab = proper("`r'")
  7.                 if "`lab'" == "Hispa" loc lab = "Hispanic"
  8.         
.                 label var `r'_aa0 "`lab' X No Position"
  9.                 label var `r'_aa1 "`lab' X Expand"
 10.                 label var `r'_aa2 "`lab' X Keep"
 11.                 label var `r'_aa3 "`lab' X End"
 12.                 
.                 loc int "`int' `r'_aa0 `r'_aa1 `r'_aa2 `r'_aa3"
 13.         
.         }

.         // set reference
.         replace white_aa0 = 0
(560 real changes made)

.         label var noracepolicy "Not shown position"

.         
.         gen out_fair_bwdiff = out_fair_black - out_fair_white
(2 missing values generated)

.                 
. //============================================================================== Regress the things
. 
.         
.         // Respondent race
.                 eststo clear

.                 reg out_ideo `reg_distpop' `reg_race' `reg_affirm' `reg_issues' `reg_sex' cand_age `reg_
> exp' `reg_biden' if r_white == 1, vce(cluster r_id)
note: zero_dist omitted because of collinearity.
note: zero_race omitted because of collinearity.
note: zero_racepol omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: zero_sex omitted because of collinearity.
note: zero_exp omitted because of collinearity.
note: zero_biden omitted because of collinearity.

Linear regression                               Number of obs     =      5,298
                                                F(29, 1059)       =       8.72
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0476
                                                Root MSE          =     .23031

                                      (Std. err. adjusted for 1,060 clusters in r_id)
-------------------------------------------------------------------------------------
                    |               Robust
           out_ideo | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
         cand_dist1 |   -.007895   .0096265    -0.82   0.412    -.0267842    .0109942
         cand_dist2 |  -.0120122   .0095033    -1.26   0.207    -.0306596    .0066352
         cand_dist3 |  -.0148783   .0099155    -1.50   0.134    -.0343346     .004578
         cand_dist4 |  -.0156848   .0094917    -1.65   0.099    -.0343094    .0029398
         cand_dist5 |  -.0170057   .0101212    -1.68   0.093    -.0368655    .0028542
         cand_dist6 |  -.0160176    .009602    -1.67   0.096    -.0348587    .0028235
          zero_dist |          0  (omitted)
         cand_black |   .0143111   .0068602     2.09   0.037       .00085    .0277723
          zero_race |          0  (omitted)
         cand_asian |   .0079694   .0070837     1.13   0.261    -.0059304    .0218691
         cand_hispa |   .0143948   .0066301     2.17   0.030     .0013852    .0274044
    cand_policy_aa1 |   .0339384   .0095679     3.55   0.000     .0151643    .0527125
    cand_policy_aa2 |   .0282426   .0093131     3.03   0.002     .0099684    .0465169
    cand_policy_aa3 |   -.042338   .0095485    -4.43   0.000    -.0610742   -.0236019
       zero_racepol |          0  (omitted)
 cand_policy_abort1 |   .0998473   .0104971     9.51   0.000     .0792498    .1204447
 cand_policy_abort2 |   .0273799   .0098949     2.77   0.006      .007964    .0467958
   cand_policy_tax1 |    .012151   .0103675     1.17   0.241    -.0081922    .0324941
   cand_policy_tax2 |  -.0136052   .0098642    -1.38   0.168    -.0329608    .0057503
cand_policy_health1 |    .038081   .0103337     3.69   0.000     .0178042    .0583579
cand_policy_health2 |   .0090621   .0098333     0.92   0.357    -.0102328     .028357
   cand_policy_eco1 |    .016483   .0084468     1.95   0.051    -.0000913    .0330574
           zero_eco |          0  (omitted)
        cand_female |   .0056826    .005282     1.08   0.282    -.0046818     .016047
           zero_sex |          0  (omitted)
           cand_age |  -.0008333   .0005273    -1.58   0.114     -.001868    .0002015
     cand_exp_teach |   .0087106   .0075855     1.15   0.251    -.0061736    .0235949
   cand_exp_council |    .004143   .0073434     0.56   0.573    -.0102662    .0185523
    cand_exp_lawyer |   .0008453   .0075687     0.11   0.911    -.0140061    .0156967
  cand_exp_business |    .002312   .0072524     0.32   0.750    -.0119187    .0165428
           zero_exp |          0  (omitted)
     cand_biden_p59 |   .0091565   .0076271     1.20   0.230    -.0058094    .0241223
     cand_biden_p57 |   .0156873   .0074133     2.12   0.035     .0011408    .0302338
     cand_biden_p55 |   .0064727   .0076033     0.85   0.395    -.0084465    .0213919
     cand_biden_p53 |    .001897   .0072511     0.26   0.794    -.0123312    .0161253
         zero_biden |          0  (omitted)
              _cons |   .6857527   .0316275    21.68   0.000      .623693    .7478125
-------------------------------------------------------------------------------------

.                 eststo pool_ideo_w

.                 reg out_ideo `reg_distpop' `reg_race' `reg_affirm' `reg_issues' `reg_sex' cand_age `reg_
> exp' `reg_biden' if r_black == 1, vce(cluster r_id)
note: zero_dist omitted because of collinearity.
note: zero_race omitted because of collinearity.
note: zero_racepol omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: zero_sex omitted because of collinearity.
note: zero_exp omitted because of collinearity.
note: zero_biden omitted because of collinearity.

Linear regression                               Number of obs     =      1,013
                                                F(29, 202)        =       1.04
                                                Prob > F          =     0.4123
                                                R-squared         =     0.0219
                                                Root MSE          =     .26589

                                        (Std. err. adjusted for 203 clusters in r_id)
-------------------------------------------------------------------------------------
                    |               Robust
           out_ideo | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
         cand_dist1 |  -.0099843   .0257533    -0.39   0.699     -.060764    .0407954
         cand_dist2 |   .0081547   .0242917     0.34   0.737    -.0397432    .0560526
         cand_dist3 |  -.0054193   .0263596    -0.21   0.837    -.0573946     .046556
         cand_dist4 |   .0009306   .0293995     0.03   0.975    -.0570387       .0589
         cand_dist5 |   .0064362   .0262787     0.24   0.807    -.0453796     .058252
         cand_dist6 |  -.0066367   .0254987    -0.26   0.795    -.0569144     .043641
          zero_dist |          0  (omitted)
         cand_black |  -.0022902   .0180453    -0.13   0.899    -.0378715    .0332911
          zero_race |          0  (omitted)
         cand_asian |  -.0129747    .018635    -0.70   0.487    -.0497188    .0237694
         cand_hispa |   .0056263   .0191406     0.29   0.769    -.0321147    .0433673
    cand_policy_aa1 |   .0070001   .0230713     0.30   0.762    -.0384915    .0524916
    cand_policy_aa2 |   .0173885   .0253212     0.69   0.493    -.0325393    .0673162
    cand_policy_aa3 |  -.0552161   .0288151    -1.92   0.057     -.112033    .0016008
       zero_racepol |          0  (omitted)
 cand_policy_abort1 |   .0334451   .0249314     1.34   0.181    -.0157141    .0826042
 cand_policy_abort2 |  -.0010283   .0248192    -0.04   0.967    -.0499662    .0479095
   cand_policy_tax1 |   .0038967   .0256692     0.15   0.879    -.0467172    .0545106
   cand_policy_tax2 |  -.0126907   .0273012    -0.46   0.643    -.0665225    .0411412
cand_policy_health1 |   .0352082   .0231314     1.52   0.130    -.0104018    .0808183
cand_policy_health2 |   .0116251   .0249078     0.47   0.641    -.0374875    .0607377
   cand_policy_eco1 |   .0068146   .0232022     0.29   0.769     -.038935    .0525642
           zero_eco |          0  (omitted)
        cand_female |    .007851   .0150663     0.52   0.603    -.0218563    .0375583
           zero_sex |          0  (omitted)
           cand_age |   9.63e-06   .0013092     0.01   0.994    -.0025718    .0025911
     cand_exp_teach |   .0211619   .0189634     1.12   0.266    -.0162297    .0585535
   cand_exp_council |   .0045772   .0194929     0.23   0.815    -.0338585    .0430128
    cand_exp_lawyer |   .0031439   .0206378     0.15   0.879    -.0375493     .043837
  cand_exp_business |   .0018984   .0206164     0.09   0.927    -.0387526    .0425494
           zero_exp |          0  (omitted)
     cand_biden_p59 |  -.0338796   .0199879    -1.70   0.092    -.0732913     .005532
     cand_biden_p57 |  -.0024698   .0204456    -0.12   0.904     -.042784    .0378444
     cand_biden_p55 |  -.0058383   .0181903    -0.32   0.749    -.0417054    .0300289
     cand_biden_p53 |  -.0022317   .0194965    -0.11   0.909    -.0406745    .0362112
         zero_biden |          0  (omitted)
              _cons |   .5945256   .0776803     7.65   0.000     .4413572    .7476939
-------------------------------------------------------------------------------------

.                 eststo pool_ideo_b

.                 
.                 reg out_fair_bwdiff `reg_distpop' `reg_race' `reg_affirm' `reg_issues' `reg_sex' cand_ag
> e `reg_exp' `reg_biden' if r_white == 1, vce(cluster r_id)
note: zero_dist omitted because of collinearity.
note: zero_race omitted because of collinearity.
note: zero_racepol omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: zero_sex omitted because of collinearity.
note: zero_exp omitted because of collinearity.
note: zero_biden omitted because of collinearity.

Linear regression                               Number of obs     =      5,298
                                                F(29, 1059)       =      12.21
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0768
                                                Root MSE          =     .35951

                                      (Std. err. adjusted for 1,060 clusters in r_id)
-------------------------------------------------------------------------------------
                    |               Robust
    out_fair_bwdiff | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
         cand_dist1 |   .0515942   .0162333     3.18   0.002     .0197411    .0834473
         cand_dist2 |   .0786656   .0170904     4.60   0.000     .0451307    .1122006
         cand_dist3 |    .077971   .0176344     4.42   0.000     .0433687    .1125734
         cand_dist4 |   .0347003   .0160124     2.17   0.030     .0032807      .06612
         cand_dist5 |   .0031943   .0169835     0.19   0.851    -.0301309    .0365195
         cand_dist6 |   .0322194   .0162718     1.98   0.048     .0002908     .064148
          zero_dist |          0  (omitted)
         cand_black |   .2074333   .0138979    14.93   0.000     .1801628    .2347038
          zero_race |          0  (omitted)
         cand_asian |   .0660357   .0113625     5.81   0.000     .0437401    .0883312
         cand_hispa |   .0764256   .0116346     6.57   0.000     .0535961    .0992551
    cand_policy_aa1 |   .0684356   .0148931     4.60   0.000     .0392123    .0976589
    cand_policy_aa2 |   .0641347   .0141748     4.52   0.000     .0363209    .0919485
    cand_policy_aa3 |  -.0622403   .0133904    -4.65   0.000     -.088515   -.0359656
       zero_racepol |          0  (omitted)
 cand_policy_abort1 |    .019111   .0149744     1.28   0.202    -.0102718    .0484938
 cand_policy_abort2 |   .0040958   .0146078     0.28   0.779    -.0245677    .0327593
   cand_policy_tax1 |   .0208704   .0148697     1.40   0.161     -.008307    .0500477
   cand_policy_tax2 |   .0094509   .0153253     0.62   0.538    -.0206205    .0395224
cand_policy_health1 |   .0206652   .0151903     1.36   0.174    -.0091414    .0504718
cand_policy_health2 |   .0201166   .0149516     1.35   0.179    -.0092217    .0494548
   cand_policy_eco1 |   .0299991    .013295     2.26   0.024     .0039115    .0560867
           zero_eco |          0  (omitted)
        cand_female |   .0172104   .0086261     2.00   0.046     .0002842    .0341365
           zero_sex |          0  (omitted)
           cand_age |   .0001374   .0008285     0.17   0.868    -.0014884    .0017631
     cand_exp_teach |  -.0016206   .0125049    -0.13   0.897    -.0261578    .0229165
   cand_exp_council |    .011601   .0126813     0.91   0.360    -.0132823    .0364842
    cand_exp_lawyer |  -.0149161   .0131054    -1.14   0.255    -.0406316    .0107994
  cand_exp_business |    -.01314    .012819    -1.03   0.306    -.0382936    .0120136
           zero_exp |          0  (omitted)
     cand_biden_p59 |   .0135988   .0128953     1.05   0.292    -.0117044    .0389021
     cand_biden_p57 |   .0017955   .0126891     0.14   0.888    -.0231033    .0266942
     cand_biden_p55 |   .0161162   .0131679     1.22   0.221    -.0097219    .0419543
     cand_biden_p53 |   .0101448   .0129996     0.78   0.435     -.015363    .0356527
         zero_biden |          0  (omitted)
              _cons |  -.0842213   .0484792    -1.74   0.083    -.1793476     .010905
-------------------------------------------------------------------------------------

.                 eststo pool_fair_w

.                 reg out_fair_bwdiff `reg_distpop' `reg_race' `reg_affirm' `reg_issues' `reg_sex' cand_ag
> e `reg_exp' `reg_biden' if r_black == 1, vce(cluster r_id)
note: zero_dist omitted because of collinearity.
note: zero_race omitted because of collinearity.
note: zero_racepol omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: zero_sex omitted because of collinearity.
note: zero_exp omitted because of collinearity.
note: zero_biden omitted because of collinearity.

Linear regression                               Number of obs     =      1,015
                                                F(29, 202)        =       2.46
                                                Prob > F          =     0.0001
                                                R-squared         =     0.0612
                                                Root MSE          =     .42551

                                        (Std. err. adjusted for 203 clusters in r_id)
-------------------------------------------------------------------------------------
                    |               Robust
    out_fair_bwdiff | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
         cand_dist1 |   .0046141   .0493682     0.09   0.926     -.092729    .1019572
         cand_dist2 |   .0739221   .0445681     1.66   0.099    -.0139562    .1618004
         cand_dist3 |   .0990717   .0508632     1.95   0.053    -.0012193    .1993626
         cand_dist4 |   .0308757    .048382     0.64   0.524    -.0645228    .1262743
         cand_dist5 |  -.0234075   .0459354    -0.51   0.611    -.1139819     .067167
         cand_dist6 |  -.0150828   .0401913    -0.38   0.708    -.0943312    .0641655
          zero_dist |          0  (omitted)
         cand_black |   .1828615   .0349903     5.23   0.000     .1138685    .2518545
          zero_race |          0  (omitted)
         cand_asian |    .118181   .0306245     3.86   0.000     .0577962    .1785657
         cand_hispa |   .0795796   .0322077     2.47   0.014     .0160732    .1430859
    cand_policy_aa1 |   .0284546   .0395655     0.72   0.473    -.0495598     .106469
    cand_policy_aa2 |  -.0067161   .0362585    -0.19   0.853    -.0782098    .0647776
    cand_policy_aa3 |  -.0850333   .0408686    -2.08   0.039     -.165617   -.0044496
       zero_racepol |          0  (omitted)
 cand_policy_abort1 |  -.0202152   .0446525    -0.45   0.651    -.1082601    .0678296
 cand_policy_abort2 |   .0112759   .0410367     0.27   0.784    -.0696394    .0921912
   cand_policy_tax1 |   .0422943   .0420119     1.01   0.315    -.0405438    .1251324
   cand_policy_tax2 |   .0449797    .039548     1.14   0.257    -.0330001    .1229595
cand_policy_health1 |  -.0159371   .0421483    -0.38   0.706    -.0990442      .06717
cand_policy_health2 |   .0619669   .0404668     1.53   0.127    -.0178246    .1417584
   cand_policy_eco1 |  -.0077906   .0419616    -0.19   0.853    -.0905295    .0749483
           zero_eco |          0  (omitted)
        cand_female |   .0172469   .0233262     0.74   0.461    -.0287472    .0632411
           zero_sex |          0  (omitted)
           cand_age |   -.001981    .001965    -1.01   0.315    -.0058556    .0018937
     cand_exp_teach |   -.042421   .0352728    -1.20   0.231    -.1119711    .0271292
   cand_exp_council |   .0046208   .0339123     0.14   0.892    -.0622466    .0714882
    cand_exp_lawyer |   .0467259   .0385548     1.21   0.227    -.0292956    .1227475
  cand_exp_business |  -.0093775   .0345051    -0.27   0.786    -.0774138    .0586588
           zero_exp |          0  (omitted)
     cand_biden_p59 |  -.0232799   .0376712    -0.62   0.537    -.0975591    .0509993
     cand_biden_p57 |   .0202763   .0350233     0.58   0.563    -.0487818    .0893344
     cand_biden_p55 |    .059937   .0344292     1.74   0.083    -.0079497    .1278238
     cand_biden_p53 |    .027291   .0331733     0.82   0.412    -.0381194    .0927014
         zero_biden |          0  (omitted)
              _cons |  -.0455129   .1275665    -0.36   0.722    -.2970457    .2060199
-------------------------------------------------------------------------------------

.                 eststo pool_fair_b

. 
.         // PID
.                 reg out_ideo `reg_distpop' `reg_race' `reg_affirm' `reg_issues' `reg_sex' cand_age `reg_
> exp' `reg_biden' if r_dem == 1, vce(cluster r_id)
note: zero_dist omitted because of collinearity.
note: zero_race omitted because of collinearity.
note: zero_racepol omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: zero_sex omitted because of collinearity.
note: zero_exp omitted because of collinearity.
note: zero_biden omitted because of collinearity.

Linear regression                               Number of obs     =      2,738
                                                F(29, 547)        =       3.39
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0357
                                                Root MSE          =     .23661

                                        (Std. err. adjusted for 548 clusters in r_id)
-------------------------------------------------------------------------------------
                    |               Robust
           out_ideo | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
         cand_dist1 |  -.0293238   .0141605    -2.07   0.039    -.0571394   -.0015082
         cand_dist2 |  -.0194743   .0134869    -1.44   0.149    -.0459667    .0070181
         cand_dist3 |  -.0178264     .01374    -1.30   0.195     -.044816    .0091633
         cand_dist4 |  -.0219207   .0150697    -1.45   0.146    -.0515222    .0076808
         cand_dist5 |  -.0205628   .0148157    -1.39   0.166    -.0496655    .0085399
         cand_dist6 |  -.0285281   .0145069    -1.97   0.050    -.0570242    -.000032
          zero_dist |          0  (omitted)
         cand_black |   .0167949   .0100058     1.68   0.094    -.0028595    .0364493
          zero_race |          0  (omitted)
         cand_asian |   .0077547   .0105871     0.73   0.464    -.0130417     .028551
         cand_hispa |   .0237054   .0097529     2.43   0.015     .0045476    .0428631
    cand_policy_aa1 |   .0305343   .0133915     2.28   0.023     .0042294    .0568393
    cand_policy_aa2 |   .0180793   .0131829     1.37   0.171    -.0078159    .0439745
    cand_policy_aa3 |  -.0438512   .0140468    -3.12   0.002    -.0714435    -.016259
       zero_racepol |          0  (omitted)
 cand_policy_abort1 |   .0641025   .0153843     4.17   0.000     .0338829     .094322
 cand_policy_abort2 |   .0136407   .0138947     0.98   0.327    -.0136528    .0409342
   cand_policy_tax1 |    .016818   .0144642     1.16   0.245    -.0115942    .0452301
   cand_policy_tax2 |  -.0278064   .0145724    -1.91   0.057    -.0564311    .0008183
cand_policy_health1 |   .0279197   .0146577     1.90   0.057    -.0008726     .056712
cand_policy_health2 |   .0082651   .0145505     0.57   0.570    -.0203165    .0368467
   cand_policy_eco1 |   .0259734   .0130015     2.00   0.046     .0004344    .0515125
           zero_eco |          0  (omitted)
        cand_female |    .008632   .0080501     1.07   0.284    -.0071809    .0244448
           zero_sex |          0  (omitted)
           cand_age |  -.0013394    .000765    -1.75   0.081    -.0028422    .0001633
     cand_exp_teach |   .0147879   .0113408     1.30   0.193    -.0074888    .0370647
   cand_exp_council |   .0057564   .0107487     0.54   0.592    -.0153573    .0268701
    cand_exp_lawyer |   .0040091   .0118495     0.34   0.735     -.019267    .0272853
  cand_exp_business |   .0064074    .010725     0.60   0.550    -.0146599    .0274746
           zero_exp |          0  (omitted)
     cand_biden_p59 |  -.0044018   .0117041    -0.38   0.707    -.0273923    .0185888
     cand_biden_p57 |  -.0019039   .0111749    -0.17   0.865    -.0238548     .020047
     cand_biden_p55 |   .0022214   .0107136     0.21   0.836    -.0188234    .0232663
     cand_biden_p53 |  -.0076708   .0109974    -0.70   0.486    -.0292732    .0139316
         zero_biden |          0  (omitted)
              _cons |   .7088676   .0461937    15.35   0.000     .6181289    .7996063
-------------------------------------------------------------------------------------

.                 eststo pool_ideo_d

.                 reg out_ideo `reg_distpop' `reg_race' `reg_affirm' `reg_issues' `reg_sex' cand_age `reg_
> exp' `reg_biden' if r_gop == 1, vce(cluster r_id)
note: zero_dist omitted because of collinearity.
note: zero_race omitted because of collinearity.
note: zero_racepol omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: zero_sex omitted because of collinearity.
note: zero_exp omitted because of collinearity.
note: zero_biden omitted because of collinearity.

Linear regression                               Number of obs     =      2,275
                                                F(29, 454)        =       3.39
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0346
                                                Root MSE          =     .24665

                                        (Std. err. adjusted for 455 clusters in r_id)
-------------------------------------------------------------------------------------
                    |               Robust
           out_ideo | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
         cand_dist1 |   .0009622   .0154865     0.06   0.950    -.0294718    .0313963
         cand_dist2 |   .0111025   .0151914     0.73   0.465    -.0187516    .0409566
         cand_dist3 |  -.0331709   .0158233    -2.10   0.037    -.0642669   -.0020749
         cand_dist4 |   .0046102   .0153936     0.30   0.765    -.0256413    .0348618
         cand_dist5 |  -.0155732   .0167631    -0.93   0.353    -.0485162    .0173697
         cand_dist6 |  -.0126465   .0151067    -0.84   0.403    -.0423343    .0170413
          zero_dist |          0  (omitted)
         cand_black |  -.0123607   .0103165    -1.20   0.231    -.0326346    .0079132
          zero_race |          0  (omitted)
         cand_asian |   -.005479   .0103205    -0.53   0.596    -.0257608    .0148028
         cand_hispa |   .0019337   .0100303     0.19   0.847    -.0177779    .0216452
    cand_policy_aa1 |   .0150583   .0154581     0.97   0.331      -.01532    .0454365
    cand_policy_aa2 |   .0248757   .0161175     1.54   0.123    -.0067984    .0565499
    cand_policy_aa3 |  -.0370848   .0158591    -2.34   0.020    -.0682511   -.0059185
       zero_racepol |          0  (omitted)
 cand_policy_abort1 |   .0779725   .0168496     4.63   0.000     .0448596    .1110854
 cand_policy_abort2 |   .0205779   .0159068     1.29   0.196    -.0106821     .051838
   cand_policy_tax1 |  -.0059335   .0166172    -0.36   0.721    -.0385897    .0267228
   cand_policy_tax2 |  -.0239566   .0161034    -1.49   0.138     -.055603    .0076898
cand_policy_health1 |   .0323267    .015785     2.05   0.041     .0013061    .0633473
cand_policy_health2 |  -.0051907   .0154508    -0.34   0.737    -.0355546    .0251731
   cand_policy_eco1 |   .0055955   .0137744     0.41   0.685    -.0214741     .032665
           zero_eco |          0  (omitted)
        cand_female |   .0072118   .0081292     0.89   0.375    -.0087637    .0231874
           zero_sex |          0  (omitted)
           cand_age |  -.0005068   .0008868    -0.57   0.568    -.0022495    .0012359
     cand_exp_teach |    .006657   .0115096     0.58   0.563    -.0159617    .0292757
   cand_exp_council |  -.0002436   .0112501    -0.02   0.983    -.0223524    .0218651
    cand_exp_lawyer |  -.0009196   .0112384    -0.08   0.935    -.0230053     .021166
  cand_exp_business |   .0130365   .0111256     1.17   0.242    -.0088276    .0349006
           zero_exp |          0  (omitted)
     cand_biden_p59 |   .0167575   .0112855     1.48   0.138    -.0054208    .0389359
     cand_biden_p57 |   .0239326   .0117557     2.04   0.042     .0008303    .0470349
     cand_biden_p55 |   .0124084   .0115839     1.07   0.285    -.0103563    .0351731
     cand_biden_p53 |   .0200121   .0104984     1.91   0.057    -.0006193    .0406435
         zero_biden |          0  (omitted)
              _cons |   .7105251   .0534352    13.30   0.000      .605514    .8155362
-------------------------------------------------------------------------------------

.                 eststo pool_ideo_r

.         
.                 loc b_pool_fair = string(round(_b[_cons], 0.001), "%9.3f")

.                 reg out_fair_bwdiff `reg_distpop' `reg_race' `reg_affirm' `reg_issues' `reg_sex' cand_ag
> e `reg_exp' `reg_biden' if r_dem == 1, vce(cluster r_id)
note: zero_dist omitted because of collinearity.
note: zero_race omitted because of collinearity.
note: zero_racepol omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: zero_sex omitted because of collinearity.
note: zero_exp omitted because of collinearity.
note: zero_biden omitted because of collinearity.

Linear regression                               Number of obs     =      2,738
                                                F(29, 547)        =       6.00
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0762
                                                Root MSE          =     .33422

                                        (Std. err. adjusted for 548 clusters in r_id)
-------------------------------------------------------------------------------------
                    |               Robust
    out_fair_bwdiff | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
         cand_dist1 |   .0268623   .0214622     1.25   0.211    -.0152961    .0690206
         cand_dist2 |   .0583105   .0231233     2.52   0.012     .0128891    .1037319
         cand_dist3 |   .0888743   .0230235     3.86   0.000      .043649    .1340997
         cand_dist4 |  -.0118364   .0222793    -0.53   0.595    -.0555998     .031927
         cand_dist5 |   .0138068   .0217919     0.63   0.527    -.0289993    .0566128
         cand_dist6 |   .0005955   .0222633     0.03   0.979    -.0431366    .0443275
          zero_dist |          0  (omitted)
         cand_black |   .1788502   .0181141     9.87   0.000     .1432685    .2144318
          zero_race |          0  (omitted)
         cand_asian |   .0847866   .0152836     5.55   0.000     .0547648    .1148084
         cand_hispa |   .0791783   .0166675     4.75   0.000     .0464381    .1119185
    cand_policy_aa1 |   .0633199   .0191232     3.31   0.001     .0257559    .1008839
    cand_policy_aa2 |   .0396702   .0175012     2.27   0.024     .0052923     .074048
    cand_policy_aa3 |  -.0708978   .0194369    -3.65   0.000    -.1090779   -.0327178
       zero_racepol |          0  (omitted)
 cand_policy_abort1 |   .0078446   .0196643     0.40   0.690    -.0307821    .0464714
 cand_policy_abort2 |  -.0066241   .0193855    -0.34   0.733    -.0447032     .031455
   cand_policy_tax1 |   .0321151   .0193606     1.66   0.098     -.005915    .0701453
   cand_policy_tax2 |   .0029544   .0198402     0.15   0.882    -.0360179    .0419268
cand_policy_health1 |  -.0047321   .0203001    -0.23   0.816    -.0446079    .0351437
cand_policy_health2 |   .0265776   .0191113     1.39   0.165     -.010963    .0641182
   cand_policy_eco1 |   .0163355   .0186922     0.87   0.383    -.0203817    .0530527
           zero_eco |          0  (omitted)
        cand_female |   .0187498   .0112684     1.66   0.097    -.0033848    .0408844
           zero_sex |          0  (omitted)
           cand_age |  -.0009994   .0010867    -0.92   0.358    -.0031341    .0011352
     cand_exp_teach |  -.0196595    .017453    -1.13   0.260    -.0539425    .0146235
   cand_exp_council |   .0074545   .0174322     0.43   0.669    -.0267876    .0416967
    cand_exp_lawyer |    .006198   .0184821     0.34   0.737    -.0301067    .0425026
  cand_exp_business |   .0005013   .0181539     0.03   0.978    -.0351586    .0361611
           zero_exp |          0  (omitted)
     cand_biden_p59 |   .0073694   .0183311     0.40   0.688    -.0286385    .0433773
     cand_biden_p57 |   .0083564   .0172424     0.48   0.628     -.025513    .0422259
     cand_biden_p55 |   .0123925    .018118     0.68   0.494    -.0231968    .0479818
     cand_biden_p53 |   .0048032   .0177783     0.27   0.787    -.0301189    .0397253
         zero_biden |          0  (omitted)
              _cons |  -.0631782   .0627928    -1.01   0.315    -.1865228    .0601664
-------------------------------------------------------------------------------------

.                 eststo pool_fair_d

.                 reg out_fair_bwdiff `reg_distpop' `reg_race' `reg_affirm' `reg_issues' `reg_sex' cand_ag
> e `reg_exp' `reg_biden' if r_gop == 1, vce(cluster r_id)
note: zero_dist omitted because of collinearity.
note: zero_race omitted because of collinearity.
note: zero_racepol omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: zero_sex omitted because of collinearity.
note: zero_exp omitted because of collinearity.
note: zero_biden omitted because of collinearity.

Linear regression                               Number of obs     =      2,275
                                                F(29, 454)        =       5.68
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0679
                                                Root MSE          =     .38829

                                        (Std. err. adjusted for 455 clusters in r_id)
-------------------------------------------------------------------------------------
                    |               Robust
    out_fair_bwdiff | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
         cand_dist1 |   .0753216   .0263507     2.86   0.004      .023537    .1271062
         cand_dist2 |   .1086317   .0284321     3.82   0.000     .0527568    .1645066
         cand_dist3 |   .0799779   .0302404     2.64   0.008     .0205494    .1394064
         cand_dist4 |   .0912772     .02564     3.56   0.000     .0408894    .1416649
         cand_dist5 |   .0286303   .0299704     0.96   0.340    -.0302676    .0875282
         cand_dist6 |   .0606525   .0264748     2.29   0.022     .0086241     .112681
          zero_dist |          0  (omitted)
         cand_black |   .1937093   .0226926     8.54   0.000     .1491137    .2383049
          zero_race |          0  (omitted)
         cand_asian |   .0348862   .0188706     1.85   0.065    -.0021984    .0719708
         cand_hispa |   .0295452   .0186672     1.58   0.114    -.0071396      .06623
    cand_policy_aa1 |   .0209855   .0242467     0.87   0.387    -.0266641    .0686351
    cand_policy_aa2 |   .0577366   .0237634     2.43   0.016     .0110366    .1044365
    cand_policy_aa3 |  -.0772939    .021649    -3.57   0.000    -.1198385   -.0347492
       zero_racepol |          0  (omitted)
 cand_policy_abort1 |   .0363711   .0259564     1.40   0.162    -.0146385    .0873807
 cand_policy_abort2 |   .0098673   .0242172     0.41   0.684    -.0377244    .0574591
   cand_policy_tax1 |    .032875   .0245221     1.34   0.181    -.0153158    .0810659
   cand_policy_tax2 |    .020179   .0236725     0.85   0.394    -.0263422    .0667003
cand_policy_health1 |   .0067825   .0241867     0.28   0.779    -.0407493    .0543144
cand_policy_health2 |   .0250434   .0239712     1.04   0.297    -.0220648    .0721517
   cand_policy_eco1 |   .0365455    .021333     1.71   0.087    -.0053783    .0784692
           zero_eco |          0  (omitted)
        cand_female |   .0123614   .0148424     0.83   0.405     -.016807    .0415297
           zero_sex |          0  (omitted)
           cand_age |   .0009983   .0013099     0.76   0.446    -.0015759    .0035725
     cand_exp_teach |  -.0174386   .0209058    -0.83   0.405    -.0585227    .0236455
   cand_exp_council |  -.0013547   .0218936    -0.06   0.951      -.04438    .0416707
    cand_exp_lawyer |  -.0408961   .0215252    -1.90   0.058    -.0831975    .0014052
  cand_exp_business |  -.0144663   .0205041    -0.71   0.481    -.0547611    .0258284
           zero_exp |          0  (omitted)
     cand_biden_p59 |   .0326719   .0223772     1.46   0.145    -.0113039    .0766476
     cand_biden_p57 |   .0283308   .0215559     1.31   0.189    -.0140309    .0706925
     cand_biden_p55 |   .0537717   .0219241     2.45   0.015     .0106865    .0968569
     cand_biden_p53 |   .0196391   .0213947     0.92   0.359    -.0224058    .0616839
         zero_biden |          0  (omitted)
              _cons |  -.0853721   .0792072    -1.08   0.282    -.2410304    .0702862
-------------------------------------------------------------------------------------

.                 eststo pool_fair_r

.                 
.         // Plot pooled model
.                 coefplot (pool_ideo_w, label() mc(teal) ciopts(color(teal) lw(med))) ///
>                                  (pool_ideo_b, label() mc(gs4) ciopts(color(gs4) lw(med))) ///
>                                         , bylabel("{bf:(a) Ideological Liberalness}") || ///
>                                 (pool_fair_w, label() mc(teal) ciopts(color(teal) lw(med))) ///
>                                 (pool_fair_b, label() mc(gs4) ciopts(color(gs4) lw(med))) ///
>                                         , bylabel("{bf:(b) Prioritize Black over White Constituents}") /
> //
>                                 || , drop(_cons cand_age) omitted baselevels ms(c) msize(medsmall) ///
>                                 ylabel(,labsize(vsmall)) ///
>                         xline(0, lc(black))  ///
>                         subtitle(, bcolor(white) color(black) size(vsmall)) ///
>                         byopts(row(1) note("`notes'", size(vsmall)) t1title("{bf:`title'}", size(small))
> ) ///
>                         xtitle("Effects of Candidate Attributes (Scale 0 to 1)", size(vsmall)) ///
>                         xlabel(-0.2(0.1)0.2,labsize(small)) norecycle ///
>                         headings(cand_black = "{bf: Race}" ///
>                                         cand_female = "{bf: Gender}" ///
>                                         cand_exp_teach = "{bf: Occupation}" ///
>                                         cand_biden_p59 = "{bf: District Vote for Biden}" ///
>                                         cand_dist1 = "{bf: District Racial % [W,B,A,H,O]}" ///
>                                         cand_policy_abort1 = "{bf: Abortion}" ///
>                                         cand_policy_tax1 = "{bf: Tax Policy}" ///
>                                         cand_policy_health1 = "{bf: Healthcare}" ///
>                                         cand_policy_eco1 = "{bf: Energy}" ///
>                                         cand_policy_aa1 = "{bf: Affirmative Action}" ///
>                                         , labsize(vsmall)) legend(order(2 "White" 4 "Black") size(vsmall
> )) 
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)

.         
. 
.                 graph display, xsize(5) ysize(4.7) margins(vsmall)      

.                 graph export figure_s4.png, as(png) replace
(file figure_s4.png not found)
file figure_s4.png saved as PNG format

.                 
.         
.                 coefplot (pool_ideo_d, label() mc(navy) ciopts(color(navy) lw(med))) ///
>                                  (pool_ideo_r, label() mc(maroon) ciopts(color(maroon) lw(med))) ///
>                                         , bylabel("{bf:(a) Ideological Liberalness}") || ///
>                                 (pool_fair_d, label() mc(navy) ciopts(color(navy) lw(med))) ///
>                                 (pool_fair_r, label() mc(maroon) ciopts(color(maroon) lw(med))) ///
>                                         , bylabel("{bf:(b) Prioritize Black over White Constituents}") /
> //
>                                 || , drop(_cons cand_age) omitted baselevels ms(c) msize(medsmall) ///
>                                 ylabel(,labsize(vsmall)) ///
>                         xline(0, lc(black))  ///
>                         subtitle(, bcolor(white) color(black) size(vsmall)) ///
>                         byopts(row(1) note("`notes'", size(vsmall)) t1title("{bf:`title'}", size(small))
> ) ///
>                         xtitle("Effects of Candidate Attributes (Scale 0 to 1)", size(vsmall)) ///
>                         xlabel(-0.2(0.1)0.2,labsize(small)) norecycle ///
>                         headings(cand_black = "{bf: Race}" ///
>                                         cand_female = "{bf: Gender}" ///
>                                         cand_exp_teach = "{bf: Occupation}" ///
>                                         cand_biden_p59 = "{bf: District Vote for Biden}" ///
>                                         cand_dist1 = "{bf: District Racial % [W,B,A,H,O]}" ///
>                                         cand_policy_abort1 = "{bf: Abortion}" ///
>                                         cand_policy_tax1 = "{bf: Tax Policy}" ///
>                                         cand_policy_health1 = "{bf: Healthcare}" ///
>                                         cand_policy_eco1 = "{bf: Energy}" ///
>                                         cand_policy_aa1 = "{bf: Affirmative Action}" ///
>                                         , labsize(vsmall)) legend(order(2 "Democrats" 4 "Republicans") s
> ize(vsmall)) 
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)

.         
.                 graph display, xsize(5) ysize(4.7) margins(vsmall)      

.                 graph export figure_s6.png, as(png) replace
(file figure_s6.png not found)
file figure_s6.png saved as PNG format

.         
.         
.         // Effect of candidate attributes on main outcomes, interacted
.                 // Race
.                 reg out_ideo `reg_sex' `reg_exp' `reg_biden' `reg_distpop' `reg_issues' `int' cand_age i
> f r_white == 1, vce(cluster r_id)       
note: zero_sex omitted because of collinearity.
note: zero_exp omitted because of collinearity.
note: zero_biden omitted because of collinearity.
note: zero_dist omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      5,298
                                                F(38, 1059)       =       6.82
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0485
                                                Root MSE          =     .23039

                                      (Std. err. adjusted for 1,060 clusters in r_id)
-------------------------------------------------------------------------------------
                    |               Robust
           out_ideo | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |   .0058325   .0052773     1.11   0.269    -.0045228    .0161877
           zero_sex |          0  (omitted)
     cand_exp_teach |   .0087043   .0076081     1.14   0.253    -.0062244     .023633
   cand_exp_council |   .0042262   .0073672     0.57   0.566    -.0102299    .0186822
    cand_exp_lawyer |   .0012226   .0076107     0.16   0.872    -.0137112    .0161564
  cand_exp_business |   .0026542   .0073003     0.36   0.716    -.0116705    .0169789
           zero_exp |          0  (omitted)
     cand_biden_p59 |   .0090002   .0076312     1.18   0.239    -.0059738    .0239741
     cand_biden_p57 |   .0150139   .0074402     2.02   0.044     .0004147    .0296131
     cand_biden_p55 |   .0064879   .0076055     0.85   0.394    -.0084356    .0214114
     cand_biden_p53 |   .0019341    .007256     0.27   0.790    -.0123037    .0161719
         zero_biden |          0  (omitted)
         cand_dist1 |  -.0079817   .0096742    -0.83   0.410    -.0269644    .0110011
         cand_dist2 |  -.0122958    .009527    -1.29   0.197    -.0309898    .0063983
         cand_dist3 |  -.0145178   .0099442    -1.46   0.145    -.0340303    .0049947
         cand_dist4 |  -.0155256   .0095556    -1.62   0.105    -.0342756    .0032244
         cand_dist5 |  -.0166904   .0101306    -1.65   0.100    -.0365687    .0031879
         cand_dist6 |  -.0158113   .0096305    -1.64   0.101    -.0347083    .0030858
          zero_dist |          0  (omitted)
 cand_policy_abort1 |   .0997547   .0105063     9.49   0.000     .0791391    .1203703
 cand_policy_abort2 |   .0273069   .0099051     2.76   0.006      .007871    .0467428
   cand_policy_tax1 |   .0117051   .0103841     1.13   0.260    -.0086706    .0320809
   cand_policy_tax2 |  -.0138807   .0098669    -1.41   0.160    -.0332416    .0054803
cand_policy_health1 |   .0375678   .0103509     3.63   0.000     .0172573    .0578784
cand_policy_health2 |   .0086787   .0098468     0.88   0.378    -.0106427        .028
   cand_policy_eco1 |    .016272   .0084442     1.93   0.054    -.0002973    .0328413
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          white_aa1 |   .0218415   .0159119     1.37   0.170    -.0093809    .0530638
          white_aa2 |   .0102294   .0167534     0.61   0.542    -.0226442     .043103
          white_aa3 |  -.0564772   .0163301    -3.46   0.001    -.0885202   -.0244342
          black_aa0 |  -.0065243   .0153815    -0.42   0.672    -.0367059    .0236573
          black_aa1 |   .0483444    .015256     3.17   0.002     .0184091    .0782798
          black_aa2 |   .0330719   .0157456     2.10   0.036     .0021757     .063968
          black_aa3 |  -.0413273    .015461    -2.67   0.008    -.0716648   -.0109897
          asian_aa0 |  -.0114625   .0167018    -0.69   0.493    -.0442349    .0213099
          asian_aa1 |   .0224555   .0170379     1.32   0.188    -.0109765    .0558875
          asian_aa2 |   .0327394   .0170002     1.93   0.054    -.0006185    .0660974
          asian_aa3 |  -.0354202   .0169124    -2.09   0.036    -.0686058   -.0022345
          hispa_aa0 |   .0096569   .0160158     0.60   0.547    -.0217694    .0410832
          hispa_aa1 |   .0313458   .0178732     1.75   0.080    -.0037252    .0664167
          hispa_aa2 |   .0335688   .0162577     2.06   0.039     .0016679    .0654697
          hispa_aa3 |  -.0401079   .0175972    -2.28   0.023    -.0746372   -.0055786
           cand_age |  -.0008468   .0005281    -1.60   0.109     -.001883    .0001895
              _cons |   .6975114   .0324187    21.52   0.000     .6338993    .7611235
-------------------------------------------------------------------------------------

.                 eststo ideo_w

.                 reg out_ideo `reg_sex' `reg_exp' `reg_biden' `reg_distpop' `reg_issues' `int' cand_age i
> f r_black == 1, vce(cluster r_id)       
note: zero_sex omitted because of collinearity.
note: zero_exp omitted because of collinearity.
note: zero_biden omitted because of collinearity.
note: zero_dist omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      1,013
                                                F(38, 202)        =       1.17
                                                Prob > F          =     0.2463
                                                R-squared         =     0.0295
                                                Root MSE          =     .26608

                                        (Std. err. adjusted for 203 clusters in r_id)
-------------------------------------------------------------------------------------
                    |               Robust
           out_ideo | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |   .0086377   .0151449     0.57   0.569    -.0212247    .0385001
           zero_sex |          0  (omitted)
     cand_exp_teach |   .0200681    .019673     1.02   0.309    -.0187226    .0588589
   cand_exp_council |   .0018903   .0197932     0.10   0.924    -.0371375    .0409181
    cand_exp_lawyer |  -.0009624    .021019    -0.05   0.964    -.0424072    .0404823
  cand_exp_business |   .0010349   .0202341     0.05   0.959    -.0388623    .0409321
           zero_exp |          0  (omitted)
     cand_biden_p59 |  -.0376984   .0202754    -1.86   0.064    -.0776769    .0022802
     cand_biden_p57 |   -.004779   .0207026    -0.23   0.818    -.0455999    .0360419
     cand_biden_p55 |  -.0080054   .0185656    -0.43   0.667    -.0446125    .0286018
     cand_biden_p53 |  -.0024157   .0198232    -0.12   0.903    -.0415026    .0366711
         zero_biden |          0  (omitted)
         cand_dist1 |  -.0051459   .0257106    -0.20   0.842    -.0558414    .0455496
         cand_dist2 |   .0102502   .0243435     0.42   0.674    -.0377498    .0582502
         cand_dist3 |  -.0042337   .0265769    -0.16   0.874    -.0566374      .04817
         cand_dist4 |    .002748   .0298163     0.09   0.927     -.056043     .061539
         cand_dist5 |   .0093192   .0262393     0.36   0.723    -.0424189    .0610572
         cand_dist6 |  -.0049823   .0255657    -0.19   0.846    -.0553921    .0454276
          zero_dist |          0  (omitted)
 cand_policy_abort1 |   .0370835   .0250798     1.48   0.141    -.0123683    .0865352
 cand_policy_abort2 |   .0027433   .0247947     0.11   0.912    -.0461464    .0516329
   cand_policy_tax1 |   .0072807   .0258011     0.28   0.778    -.0435934    .0581547
   cand_policy_tax2 |  -.0090199   .0270634    -0.33   0.739    -.0623828     .044343
cand_policy_health1 |   .0356977   .0235125     1.52   0.131    -.0106637    .0820591
cand_policy_health2 |   .0113424   .0249227     0.46   0.650    -.0377997    .0604845
   cand_policy_eco1 |   .0087201   .0231757     0.38   0.707    -.0369772    .0544173
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          white_aa1 |  -.0156585   .0479667    -0.33   0.744     -.110238    .0789211
          white_aa2 |  -.0026712   .0431902    -0.06   0.951    -.0878327    .0824903
          white_aa3 |  -.0546314   .0488244    -1.12   0.264    -.1509023    .0416395
          black_aa0 |   .0065539   .0398188     0.16   0.869      -.07196    .0850677
          black_aa1 |  -.0069294   .0386863    -0.18   0.858    -.0832102    .0693514
          black_aa2 |  -.0187925   .0402463    -0.47   0.641    -.0981493    .0605642
          black_aa3 |  -.0567391    .047827    -1.19   0.237    -.1510433     .037565
          asian_aa0 |  -.0331105   .0423893    -0.78   0.436    -.1166926    .0504717
          asian_aa1 |   -.050651   .0469402    -1.08   0.282    -.1432067    .0419046
          asian_aa2 |   .0383768   .0479539     0.80   0.424    -.0561777    .1329312
          asian_aa3 |  -.0754911   .0438355    -1.72   0.087    -.1619249    .0109427
          hispa_aa0 |   -.034349   .0422863    -0.81   0.418    -.1177283    .0490302
          hispa_aa1 |   .0613846   .0491436     1.25   0.213    -.0355157    .1582849
          hispa_aa2 |   .0257014   .0443238     0.58   0.563    -.0616954    .1130981
          hispa_aa3 |  -.1003194   .0502938    -1.99   0.047    -.1994876   -.0011513
           cand_age |   .0001284   .0013234     0.10   0.923    -.0024811    .0027379
              _cons |   .5967734   .0807984     7.39   0.000      .437457    .7560899
-------------------------------------------------------------------------------------

.                 eststo ideo_b

.                 
.                 reg out_fair_bwdiff `reg_sex' `reg_exp' `reg_biden' `reg_distpop' `reg_issues' `int' can
> d_age if r_white == 1, vce(cluster r_id)
note: zero_sex omitted because of collinearity.
note: zero_exp omitted because of collinearity.
note: zero_biden omitted because of collinearity.
note: zero_dist omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      5,298
                                                F(38, 1059)       =       9.50
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0777
                                                Root MSE          =     .35963

                                      (Std. err. adjusted for 1,060 clusters in r_id)
-------------------------------------------------------------------------------------
                    |               Robust
    out_fair_bwdiff | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |   .0171435    .008633     1.99   0.047     .0002037    .0340833
           zero_sex |          0  (omitted)
     cand_exp_teach |  -.0013399   .0125649    -0.11   0.915    -.0259949     .023315
   cand_exp_council |   .0117918   .0127136     0.93   0.354    -.0131549    .0367384
    cand_exp_lawyer |  -.0146248   .0131734    -1.11   0.267    -.0404738    .0112242
  cand_exp_business |  -.0123049   .0129107    -0.95   0.341    -.0376383    .0130285
           zero_exp |          0  (omitted)
     cand_biden_p59 |   .0138005   .0129083     1.07   0.285    -.0115282    .0391292
     cand_biden_p57 |   .0009247   .0126948     0.07   0.942     -.023985    .0258345
     cand_biden_p55 |   .0160077   .0132034     1.21   0.226    -.0099001    .0419155
     cand_biden_p53 |   .0101022   .0130855     0.77   0.440    -.0155743    .0357787
         zero_biden |          0  (omitted)
         cand_dist1 |   .0502697   .0162561     3.09   0.002     .0183718    .0821676
         cand_dist2 |   .0773008   .0171502     4.51   0.000     .0436485    .1109531
         cand_dist3 |   .0774836   .0176049     4.40   0.000     .0429392    .1120281
         cand_dist4 |   .0338235   .0159988     2.11   0.035     .0024306    .0652163
         cand_dist5 |   .0025187   .0170402     0.15   0.883    -.0309177    .0359551
         cand_dist6 |   .0318059    .016328     1.95   0.052    -.0002329    .0638448
          zero_dist |          0  (omitted)
 cand_policy_abort1 |   .0184448    .015014     1.23   0.220    -.0110158    .0479055
 cand_policy_abort2 |   .0038001   .0146163     0.26   0.795    -.0248801    .0324802
   cand_policy_tax1 |   .0199973   .0149962     1.33   0.183    -.0094284     .049423
   cand_policy_tax2 |   .0091076   .0153689     0.59   0.554    -.0210493    .0392646
cand_policy_health1 |   .0193363   .0151857     1.27   0.203    -.0104613    .0491339
cand_policy_health2 |   .0189807   .0149924     1.27   0.206    -.0104375    .0483988
   cand_policy_eco1 |   .0289776   .0133182     2.18   0.030     .0028445    .0551106
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          white_aa1 |   .0576647   .0259385     2.22   0.026      .006768    .1085613
          white_aa2 |   .0546598   .0263662     2.07   0.038     .0029239    .1063958
          white_aa3 |  -.0904657   .0248146    -3.65   0.000     -.139157   -.0417744
          black_aa0 |   .1894921   .0263478     7.19   0.000     .1377922     .241192
          black_aa1 |   .2733296   .0267896    10.20   0.000     .2207629    .3258963
          black_aa2 |   .2611034   .0261861     9.97   0.000     .2097209    .3124859
          black_aa3 |   .1293892    .024839     5.21   0.000     .0806501    .1781284
          asian_aa0 |   .0402918   .0232089     1.74   0.083    -.0052487    .0858324
          asian_aa1 |   .1018824   .0264684     3.85   0.000     .0499459    .1538189
          asian_aa2 |    .121312   .0265055     4.58   0.000     .0693026    .1733213
          asian_aa3 |    .023391   .0241205     0.97   0.332    -.0239384    .0707204
          hispa_aa0 |   .0694174   .0229204     3.03   0.003     .0244429    .1143919
          hispa_aa1 |   .1382219   .0268613     5.15   0.000     .0855144    .1909293
          hispa_aa2 |   .1207061   .0262411     4.60   0.000     .0692156    .1721966
          hispa_aa3 |   .0000643   .0257018     0.00   0.998    -.0503679    .0504965
           cand_age |   .0001517   .0008293     0.18   0.855    -.0014755    .0017789
              _cons |  -.0713286   .0509103    -1.40   0.161     -.171225    .0285679
-------------------------------------------------------------------------------------

.                 eststo fair_bwdiff_w

.                 reg out_fair_bwdiff `reg_sex' `reg_exp' `reg_biden' `reg_distpop' `reg_issues' `int' can
> d_age if r_black == 1, vce(cluster r_id)
note: zero_sex omitted because of collinearity.
note: zero_exp omitted because of collinearity.
note: zero_biden omitted because of collinearity.
note: zero_dist omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      1,015
                                                F(38, 202)        =       2.08
                                                Prob > F          =     0.0007
                                                R-squared         =     0.0645
                                                Root MSE          =     .42672

                                        (Std. err. adjusted for 203 clusters in r_id)
-------------------------------------------------------------------------------------
                    |               Robust
    out_fair_bwdiff | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |   .0158581   .0238281     0.67   0.506    -.0311256    .0628417
           zero_sex |          0  (omitted)
     cand_exp_teach |  -.0437781   .0353389    -1.24   0.217    -.1134585    .0259023
   cand_exp_council |   .0062815   .0341736     0.18   0.854    -.0611013    .0736643
    cand_exp_lawyer |   .0485724   .0389567     1.25   0.214    -.0282415    .1253862
  cand_exp_business |  -.0083959   .0345163    -0.24   0.808    -.0764544    .0596626
           zero_exp |          0  (omitted)
     cand_biden_p59 |  -.0239809    .037719    -0.64   0.526    -.0983544    .0503926
     cand_biden_p57 |   .0221706   .0352594     0.63   0.530    -.0473531    .0916943
     cand_biden_p55 |   .0593944    .035336     1.68   0.094    -.0102804    .1290691
     cand_biden_p53 |   .0257933   .0332443     0.78   0.439    -.0397572    .0913437
         zero_biden |          0  (omitted)
         cand_dist1 |   .0037445   .0500101     0.07   0.940    -.0948642    .1023532
         cand_dist2 |    .077071   .0448666     1.72   0.087     -.011396    .1655379
         cand_dist3 |   .1012457   .0508811     1.99   0.048     .0009195    .2015719
         cand_dist4 |   .0338504   .0492594     0.69   0.493    -.0632783    .1309791
         cand_dist5 |  -.0233792   .0473689    -0.49   0.622      -.11678    .0700217
         cand_dist6 |  -.0147099   .0412193    -0.36   0.722    -.0959852    .0665654
          zero_dist |          0  (omitted)
 cand_policy_abort1 |  -.0192524   .0442027    -0.44   0.664    -.1064102    .0679054
 cand_policy_abort2 |   .0095706   .0410833     0.23   0.816    -.0714365    .0905776
   cand_policy_tax1 |   .0429438   .0422517     1.02   0.311    -.0403671    .1262547
   cand_policy_tax2 |   .0441741   .0397234     1.11   0.267    -.0341515    .1224998
cand_policy_health1 |   -.015516   .0418754    -0.37   0.711    -.0980848    .0670529
cand_policy_health2 |   .0616761    .039961     1.54   0.124    -.0171181    .1404703
   cand_policy_eco1 |  -.0087145    .042086    -0.21   0.836    -.0916988    .0742698
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          white_aa1 |   .0229713   .0740769     0.31   0.757    -.1230919    .1690346
          white_aa2 |  -.0204102   .0671583    -0.30   0.762    -.1528313     .112011
          white_aa3 |  -.1523109   .0695987    -2.19   0.030    -.2895441   -.0150777
          black_aa0 |   .1560819    .068033     2.29   0.023     .0219359    .2902278
          black_aa1 |   .1912098   .0626755     3.05   0.003     .0676276    .3147919
          black_aa2 |   .1474249   .0651497     2.26   0.025     .0189642    .2758855
          black_aa3 |   .0974811   .0754374     1.29   0.198    -.0512646    .2462268
          asian_aa0 |   .1191704   .0674111     1.77   0.079    -.0137493      .25209
          asian_aa1 |     .12965   .0750486     1.73   0.086    -.0183291    .2776292
          asian_aa2 |   .0695661   .0736367     0.94   0.346    -.0756291    .2147614
          asian_aa3 |   .0019491   .0738035     0.03   0.979    -.1435748    .1474731
          hispa_aa0 |   .0173371   .0614879     0.28   0.778    -.1039034    .1385776
          hispa_aa1 |   .0517911   .0775832     0.67   0.505    -.1011857    .2047679
          hispa_aa2 |   .0703009   .0648131     1.08   0.279    -.0574961    .1980979
          hispa_aa3 |    .034769   .0779055     0.45   0.656    -.1188433    .1883813
           cand_age |  -.0020503   .0019959    -1.03   0.306    -.0059858    .0018851
              _cons |  -.0213297   .1277683    -0.17   0.868    -.2732603     .230601
-------------------------------------------------------------------------------------

.                 eststo fair_bwdiff_b

.                 
.                 
.                 // PID
.                 reg out_ideo `reg_sex' `reg_exp' `reg_biden' `reg_distpop' `reg_issues' `int' cand_age i
> f r_dem == 1, vce(cluster r_id) 
note: zero_sex omitted because of collinearity.
note: zero_exp omitted because of collinearity.
note: zero_biden omitted because of collinearity.
note: zero_dist omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      2,738
                                                F(38, 547)        =       2.88
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0381
                                                Root MSE          =     .23672

                                        (Std. err. adjusted for 548 clusters in r_id)
-------------------------------------------------------------------------------------
                    |               Robust
           out_ideo | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |   .0084434   .0081056     1.04   0.298    -.0074784    .0243653
           zero_sex |          0  (omitted)
     cand_exp_teach |   .0141477   .0114642     1.23   0.218    -.0083716     .036667
   cand_exp_council |   .0052908   .0107738     0.49   0.624    -.0158723    .0264538
    cand_exp_lawyer |   .0030102   .0119291     0.25   0.801    -.0204222    .0264427
  cand_exp_business |   .0064833   .0107581     0.60   0.547     -.014649    .0276155
           zero_exp |          0  (omitted)
     cand_biden_p59 |  -.0041957   .0116969    -0.36   0.720    -.0271721    .0187807
     cand_biden_p57 |  -.0026346   .0111976    -0.24   0.814    -.0246301    .0193609
     cand_biden_p55 |   .0018124   .0107033     0.17   0.866    -.0192122     .022837
     cand_biden_p53 |  -.0081086    .010985    -0.74   0.461    -.0296866    .0134695
         zero_biden |          0  (omitted)
         cand_dist1 |  -.0292757   .0142783    -2.05   0.041    -.0573227   -.0012287
         cand_dist2 |  -.0202451   .0136249    -1.49   0.138    -.0470087    .0065185
         cand_dist3 |   -.018474   .0138553    -1.33   0.183    -.0456902    .0087421
         cand_dist4 |  -.0220317    .015318    -1.44   0.151    -.0521209    .0080576
         cand_dist5 |  -.0211875   .0149063    -1.42   0.156    -.0504682    .0080932
         cand_dist6 |  -.0293634   .0146239    -2.01   0.045    -.0580892   -.0006376
          zero_dist |          0  (omitted)
 cand_policy_abort1 |    .063638   .0153665     4.14   0.000     .0334534    .0938226
 cand_policy_abort2 |   .0131744   .0139019     0.95   0.344    -.0141332     .040482
   cand_policy_tax1 |   .0165439   .0144021     1.15   0.251    -.0117463    .0448342
   cand_policy_tax2 |  -.0280223   .0144985    -1.93   0.054    -.0565019    .0004572
cand_policy_health1 |   .0280616   .0146174     1.92   0.055    -.0006515    .0567746
cand_policy_health2 |   .0078001   .0145092     0.54   0.591    -.0207004    .0363006
   cand_policy_eco1 |   .0252516   .0130122     1.94   0.053    -.0003084    .0508116
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          white_aa1 |   .0410121   .0240484     1.71   0.089    -.0062264    .0882506
          white_aa2 |   .0129433   .0254672     0.51   0.611    -.0370822    .0629689
          white_aa3 |  -.0557251   .0243989    -2.28   0.023    -.1036522    -.007798
          black_aa0 |   .0106183   .0227107     0.47   0.640    -.0339925    .0552291
          black_aa1 |   .0541264   .0217145     2.49   0.013     .0114723    .0967805
          black_aa2 |    .024407   .0230925     1.06   0.291    -.0209539    .0697679
          black_aa3 |  -.0258746   .0230932    -1.12   0.263    -.0712369    .0194876
          asian_aa0 |    .012431   .0246176     0.50   0.614    -.0359256    .0607876
          asian_aa1 |  -.0024574    .025363    -0.10   0.923    -.0522781    .0473633
          asian_aa2 |   .0421935   .0245569     1.72   0.086    -.0060438    .0904309
          asian_aa3 |  -.0242304   .0241408    -1.00   0.316    -.0716505    .0231897
          hispa_aa0 |   .0207239   .0230838     0.90   0.370    -.0246199    .0660677
          hispa_aa1 |   .0565139   .0264839     2.13   0.033     .0044913    .1085365
          hispa_aa2 |   .0416455   .0248632     1.67   0.095    -.0071935    .0904845
          hispa_aa3 |  -.0248847   .0257259    -0.97   0.334    -.0754183     .025649
           cand_age |  -.0013709   .0007672    -1.79   0.075    -.0028779    .0001361
              _cons |   .7137985   .0486796    14.66   0.000     .6181768    .8094203
-------------------------------------------------------------------------------------

.                 eststo ideo_d

.                 reg out_ideo `reg_sex' `reg_exp' `reg_biden' `reg_distpop' `reg_issues' `int' cand_age i
> f r_gop == 1, vce(cluster r_id) 
note: zero_sex omitted because of collinearity.
note: zero_exp omitted because of collinearity.
note: zero_biden omitted because of collinearity.
note: zero_dist omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      2,275
                                                F(38, 454)        =       2.75
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0369
                                                Root MSE          =     .24685

                                        (Std. err. adjusted for 455 clusters in r_id)
-------------------------------------------------------------------------------------
                    |               Robust
           out_ideo | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |   .0070682    .008188     0.86   0.388    -.0090228    .0231593
           zero_sex |          0  (omitted)
     cand_exp_teach |   .0076794   .0116043     0.66   0.508    -.0151255    .0304843
   cand_exp_council |  -.0004888   .0114059    -0.04   0.966    -.0229037     .021926
    cand_exp_lawyer |  -.0001061   .0113541    -0.01   0.993    -.0224192     .022207
  cand_exp_business |   .0131855   .0112971     1.17   0.244    -.0090156    .0353866
           zero_exp |          0  (omitted)
     cand_biden_p59 |   .0160052   .0113216     1.41   0.158     -.006244    .0382544
     cand_biden_p57 |   .0224692   .0118702     1.89   0.059    -.0008583    .0457966
     cand_biden_p55 |   .0121779   .0117708     1.03   0.301     -.010954    .0353099
     cand_biden_p53 |   .0193786    .010742     1.80   0.072    -.0017317    .0404888
         zero_biden |          0  (omitted)
         cand_dist1 |  -.0006093   .0155244    -0.04   0.969    -.0311179    .0298993
         cand_dist2 |   .0102619   .0153727     0.67   0.505    -.0199486    .0404723
         cand_dist3 |  -.0334962   .0159956    -2.09   0.037    -.0649309   -.0020616
         cand_dist4 |   .0046955   .0154794     0.30   0.762    -.0257247    .0351156
         cand_dist5 |  -.0157108   .0167754    -0.94   0.349    -.0486778    .0172562
         cand_dist6 |   -.013102   .0152004    -0.86   0.389    -.0429739    .0167699
          zero_dist |          0  (omitted)
 cand_policy_abort1 |   .0773689   .0168936     4.58   0.000     .0441696    .1105682
 cand_policy_abort2 |   .0202408   .0158625     1.28   0.203    -.0109322    .0514139
   cand_policy_tax1 |  -.0064794   .0166716    -0.39   0.698    -.0392424    .0262837
   cand_policy_tax2 |  -.0248233   .0160804    -1.54   0.123    -.0564247     .006778
cand_policy_health1 |   .0312412   .0159444     1.96   0.051    -.0000927    .0625752
cand_policy_health2 |  -.0050417   .0155048    -0.33   0.745    -.0355118    .0254283
   cand_policy_eco1 |   .0056349   .0137217     0.41   0.682     -.021331    .0326009
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          white_aa1 |   .0039208   .0258831     0.15   0.880    -.0469447    .0547863
          white_aa2 |   -.005676   .0260788    -0.22   0.828    -.0569261     .045574
          white_aa3 |  -.0375372    .026069    -1.44   0.151    -.0887681    .0136937
          black_aa0 |  -.0277537   .0236414    -1.17   0.241    -.0742137    .0187064
          black_aa1 |   .0083214    .024761     0.34   0.737     -.040339    .0569818
          black_aa2 |  -.0011575   .0266406    -0.04   0.965    -.0535116    .0511966
          black_aa3 |  -.0650283   .0229308    -2.84   0.005     -.110092   -.0199646
          asian_aa0 |  -.0282481   .0267611    -1.06   0.292    -.0808391     .024343
          asian_aa1 |  -.0153032   .0264392    -0.58   0.563    -.0672616    .0366552
          asian_aa2 |    .024735   .0277195     0.89   0.373    -.0297395    .0792095
          asian_aa3 |  -.0392805   .0270655    -1.45   0.147    -.0924697    .0139086
          hispa_aa0 |  -.0044583   .0257539    -0.17   0.863    -.0550699    .0461532
          hispa_aa1 |   .0014299   .0265076     0.05   0.957     -.050663    .0535227
          hispa_aa2 |    .035996   .0244419     1.47   0.142    -.0120373    .0840293
          hispa_aa3 |  -.0612219   .0280912    -2.18   0.030    -.1164268   -.0060171
           cand_age |  -.0004897   .0008936    -0.55   0.584    -.0022457    .0012663
              _cons |   .7211909   .0547439    13.17   0.000     .6136081    .8287737
-------------------------------------------------------------------------------------

.                 eststo ideo_r

.                 
.                 reg out_fair_bwdiff `reg_sex' `reg_exp' `reg_biden' `reg_distpop' `reg_issues' `int' can
> d_age if r_dem == 1, vce(cluster r_id)
note: zero_sex omitted because of collinearity.
note: zero_exp omitted because of collinearity.
note: zero_biden omitted because of collinearity.
note: zero_dist omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      2,738
                                                F(38, 547)        =       4.78
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0770
                                                Root MSE          =     .33464

                                        (Std. err. adjusted for 548 clusters in r_id)
-------------------------------------------------------------------------------------
                    |               Robust
    out_fair_bwdiff | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |   .0187017   .0113012     1.65   0.099    -.0034975    .0409008
           zero_sex |          0  (omitted)
     cand_exp_teach |  -.0190871   .0175522    -1.09   0.277     -.053565    .0153908
   cand_exp_council |   .0083759   .0173767     0.48   0.630    -.0257574    .0425092
    cand_exp_lawyer |    .005964   .0185678     0.32   0.748    -.0305088    .0424369
  cand_exp_business |   .0009093   .0182598     0.05   0.960    -.0349586    .0367772
           zero_exp |          0  (omitted)
     cand_biden_p59 |   .0074301   .0185257     0.40   0.689    -.0289602    .0438203
     cand_biden_p57 |   .0082513   .0173914     0.47   0.635    -.0259108    .0424134
     cand_biden_p55 |   .0125675   .0182189     0.69   0.491    -.0232201    .0483551
     cand_biden_p53 |   .0049481   .0178062     0.28   0.781    -.0300287     .039925
         zero_biden |          0  (omitted)
         cand_dist1 |   .0265524   .0215767     1.23   0.219     -.015831    .0689357
         cand_dist2 |    .057204   .0232942     2.46   0.014     .0114471     .102961
         cand_dist3 |   .0887022   .0231923     3.82   0.000     .0431453    .1342592
         cand_dist4 |  -.0129296   .0226596    -0.57   0.569    -.0574402     .031581
         cand_dist5 |   .0122647   .0220515     0.56   0.578    -.0310512    .0555806
         cand_dist6 |   .0005763    .022532     0.03   0.980    -.0436836    .0448361
          zero_dist |          0  (omitted)
 cand_policy_abort1 |   .0085155   .0196555     0.43   0.665    -.0300941    .0471251
 cand_policy_abort2 |  -.0059111   .0194268    -0.30   0.761    -.0440713    .0322492
   cand_policy_tax1 |   .0316628    .019409     1.63   0.103    -.0064624     .069788
   cand_policy_tax2 |   .0033403   .0198342     0.17   0.866    -.0356203    .0423009
cand_policy_health1 |  -.0043956   .0203189    -0.22   0.829    -.0443083     .035517
cand_policy_health2 |   .0264428   .0191618     1.38   0.168    -.0111969    .0640824
   cand_policy_eco1 |   .0159718   .0187958     0.85   0.396    -.0209489    .0528925
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          white_aa1 |   .0528299   .0359804     1.47   0.143    -.0178468    .1235066
          white_aa2 |   .0265056   .0313332     0.85   0.398    -.0350426    .0880538
          white_aa3 |  -.0886228   .0343543    -2.58   0.010    -.1561053   -.0211404
          black_aa0 |    .149274   .0349705     4.27   0.000      .080581    .2179671
          black_aa1 |   .2344939    .031545     7.43   0.000     .1725296    .2964581
          black_aa2 |    .213571   .0351606     6.07   0.000     .1445046    .2826374
          black_aa3 |   .1085195   .0339473     3.20   0.001     .0418365    .1752025
          asian_aa0 |   .0773203   .0359258     2.15   0.032     .0067509    .1478898
          asian_aa1 |   .1245732   .0336925     3.70   0.000     .0583907    .1907557
          asian_aa2 |    .127963   .0315988     4.05   0.000     .0658932    .1900328
          asian_aa3 |   .0005189   .0349317     0.01   0.988    -.0680978    .0691355
          hispa_aa0 |   .0771974   .0302788     2.55   0.011     .0177203    .1366745
          hispa_aa1 |   .1400908   .0369478     3.79   0.000      .067514    .2126677
          hispa_aa2 |   .0908588   .0347779     2.61   0.009     .0225442    .1591733
          hispa_aa3 |  -.0023471    .035141    -0.07   0.947     -.071375    .0666808
           cand_age |  -.0009928   .0010891    -0.91   0.362    -.0031322    .0011466
              _cons |   -.053119   .0645618    -0.82   0.411    -.1799383    .0737004
-------------------------------------------------------------------------------------

.                 eststo fair_bwdiff_d

.                 reg out_fair_bwdiff `reg_sex' `reg_exp' `reg_biden' `reg_distpop' `reg_issues' `int' can
> d_age if r_gop == 1, vce(cluster r_id)
note: zero_sex omitted because of collinearity.
note: zero_exp omitted because of collinearity.
note: zero_biden omitted because of collinearity.
note: zero_dist omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      2,275
                                                F(38, 454)        =       4.74
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0723
                                                Root MSE          =     .38816

                                        (Std. err. adjusted for 455 clusters in r_id)
-------------------------------------------------------------------------------------
                    |               Robust
    out_fair_bwdiff | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
        cand_female |   .0115919   .0149038     0.78   0.437     -.017697    .0408809
           zero_sex |          0  (omitted)
     cand_exp_teach |  -.0155947    .021073    -0.74   0.460    -.0570074     .025818
   cand_exp_council |  -.0012748   .0219945    -0.06   0.954    -.0444984    .0419488
    cand_exp_lawyer |  -.0410741   .0217021    -1.89   0.059    -.0837232    .0015751
  cand_exp_business |  -.0133804   .0206428    -0.65   0.517    -.0539478     .027187
           zero_exp |          0  (omitted)
     cand_biden_p59 |   .0301538   .0224598     1.34   0.180    -.0139842    .0742919
     cand_biden_p57 |   .0255729   .0213441     1.20   0.231    -.0163727    .0675184
     cand_biden_p55 |   .0525975   .0222251     2.37   0.018     .0089207    .0962744
     cand_biden_p53 |   .0183592   .0217285     0.84   0.399    -.0243417      .06106
         zero_biden |          0  (omitted)
         cand_dist1 |   .0741217   .0265176     2.80   0.005     .0220092    .1262343
         cand_dist2 |   .1068769    .028932     3.69   0.000     .0500197    .1637341
         cand_dist3 |   .0799983    .030287     2.64   0.009     .0204782    .1395184
         cand_dist4 |   .0897815   .0260439     3.45   0.001     .0385999     .140963
         cand_dist5 |   .0273529   .0300787     0.91   0.364    -.0317578    .0864637
         cand_dist6 |    .059536      .0269     2.21   0.027      .006672    .1123999
          zero_dist |          0  (omitted)
 cand_policy_abort1 |   .0345857   .0258878     1.34   0.182    -.0162891    .0854605
 cand_policy_abort2 |   .0090206   .0242642     0.37   0.710    -.0386636    .0567047
   cand_policy_tax1 |   .0315153   .0245368     1.28   0.200    -.0167045    .0797351
   cand_policy_tax2 |   .0196024    .023838     0.82   0.411    -.0272442    .0664489
cand_policy_health1 |   .0034199   .0241774     0.14   0.888    -.0440937    .0509334
cand_policy_health2 |    .025024   .0240041     1.04   0.298    -.0221489    .0721968
   cand_policy_eco1 |   .0361006   .0212112     1.70   0.089    -.0055837     .077785
           zero_eco |          0  (omitted)
          white_aa0 |          0  (omitted)
          white_aa1 |   .0079129    .039444     0.20   0.841    -.0696026    .0854284
          white_aa2 |   .0182299   .0450325     0.40   0.686    -.0702682     .106728
          white_aa3 |  -.1348315   .0392035    -3.44   0.001    -.2118743   -.0577887
          black_aa0 |   .1728131   .0378988     4.56   0.000     .0983343    .2472918
          black_aa1 |   .2200331   .0455178     4.83   0.000     .1305814    .3094847
          black_aa2 |   .2038509   .0398089     5.12   0.000     .1256183    .2820835
          black_aa3 |   .0778013   .0397628     1.96   0.051    -.0003407    .1559434
          asian_aa0 |   -.015066   .0371676    -0.41   0.685    -.0881079    .0579759
          asian_aa1 |  -.0087204   .0441069    -0.20   0.843    -.0953994    .0779585
          asian_aa2 |    .078228   .0417049     1.88   0.061    -.0037307    .1601867
          asian_aa3 |  -.0096505   .0395224    -0.24   0.807      -.08732    .0680191
          hispa_aa0 |  -.0267622   .0368892    -0.73   0.469     -.099257    .0457326
          hispa_aa1 |   .0043914    .038907     0.11   0.910    -.0720687    .0808514
          hispa_aa2 |   .1030362   .0427899     2.41   0.016     .0189453     .187127
          hispa_aa3 |   -.060444   .0411784    -1.47   0.143    -.1413678    .0204799
           cand_age |    .000941   .0013055     0.72   0.471    -.0016245    .0035066
              _cons |  -.0524462   .0824551    -0.64   0.525    -.2144871    .1095947
-------------------------------------------------------------------------------------

.                 eststo fair_bwdiff_r

. 
.                 // Plot
.                 coefplot (ideo_w, label() mc(teal) ciopts(color(teal) lw(med))) ///
>                                  (ideo_b, label() mc(gs4) ciopts(color(gs4) lw(med))) ///
>                                         , bylabel("{bf:(a) Ideological Liberalness}") || ///
>                                 (fair_bwdiff_w, label() mc(teal) ciopts(color(teal) lw(med))) ///
>                                 (fair_bwdiff_b, label() mc(gs4) ciopts(color(gs4) lw(med))) ///
>                                         , bylabel("{bf:(b) Prioritize Black over White Constituents}") /
> //
>                                 || , drop(_cons `reg_sex' `reg_issues' cand_age `reg_exp' `reg_biden' `r
> eg_distpop') ///
>                                 omitted baselevels ms(c) msize(medsmall) ///
>                                 ylabel(,labsize(vsmall)) ///
>                         xline(0, lc(black)) legend(order(2 "White" 4 "Black") size(vsmall))  ///
>                         subtitle(, bcolor(white) color(black) size(vsmall)) ///
>                         byopts(row(1) t1title("{bf:`title'}", size(small))) ///
>                         xtitle("Effects of Candidate Attributes (Scale 0 to 1)", size(vsmall)) ///
>                         xlabel(-0.2(0.1)0.2,labsize(small)) norecycle ///
>                         headings(white_aa0 = "{bf: White X Affirmative Action}" ///
>                                         black_aa0 = "{bf: Black X Affirmative Action}" ///
>                                         asian_aa0 = "{bf: Asian X Affirmative Action}" ///
>                                         hispa_aa0 = "{bf: Hispanic X Affirmative Action}" ///
>                                         , labsize(vsmall)) 
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)

. 
.                 graph display, xsize(4.5) ysize(3.4) margins(vsmall)    

.                 graph export figure_s5.png, as(png) replace
(file figure_s5.png not found)
file figure_s5.png saved as PNG format

.                 
.         
.                 
.                 coefplot (ideo_d, label() mc(navy) ciopts(color(navy) lw(med))) ///
>                                  (ideo_r, label() mc(maroon) ciopts(color(maroon) lw(med))) ///
>                                         , bylabel("{bf:(a) Ideological Liberalness}") || ///
>                                 (fair_bwdiff_d, label() mc(navy) ciopts(color(navy) lw(med))) ///
>                                 (fair_bwdiff_r, label() mc(maroon) ciopts(color(maroon) lw(med))) ///
>                                         , bylabel("{bf:(b) Prioritize Black over White Constituents}") /
> //
>                                 || , drop(_cons `reg_sex' `reg_issues' cand_age `reg_exp' `reg_biden' `r
> eg_distpop') ///
>                                 omitted baselevels ms(c) msize(medsmall) ///
>                                 ylabel(,labsize(vsmall)) ///
>                         xline(0, lc(black)) legend(order(2 "Democrats" 4 "Republicans") size(vsmall))  /
> //
>                         subtitle(, bcolor(white) color(black) size(vsmall)) ///
>                         byopts(row(1) t1title("{bf:`title'}", size(small))) ///
>                         xtitle("Effects of Candidate Attributes (Scale 0 to 1)", size(vsmall)) ///
>                         xlabel(-0.2(0.1)0.2,labsize(small)) norecycle ///
>                         headings(white_aa0 = "{bf: White X Affirmative Action}" ///
>                                         black_aa0 = "{bf: Black X Affirmative Action}" ///
>                                         asian_aa0 = "{bf: Asian X Affirmative Action}" ///
>                                         hispa_aa0 = "{bf: Hispanic X Affirmative Action}" ///
>                                         , labsize(vsmall)) 
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)

. 
.         
.                 graph display, xsize(4.5) ysize(3.4) margins(vsmall)    

.                 graph export figure_s7.png, as(png) replace
(file figure_s7.png not found)
file figure_s7.png saved as PNG format

.                 
.         
. 
end of do-file

. do 10_appendix_figure_s8-s9.do

. /*
>         Figure S8 and S9: Majority White and Majority Black Districts
> */
. 
.         use data_study_2.dta, clear

. 
. 
. // Set omitted categories
.         gen zero_race = 0

.         label var zero_race "White"

.         gen zero_sex = 0

.         label var zero_sex "Male"

.         gen zero_eco = 0

.         label var zero_eco "Maintain investment in energy"

.         gen zero_biden = 0

.         label var zero_biden "Vote Share: 51%"

.         gen zero_exp = 0

.         label var zero_exp "Political newcomer"

.         gen zero_dist = 0

.         label var zero_dist "[28, 53, 9, 6, 4]"

.         gen zero_racepol = 0

.         label var zero_racepol "Not shown policy"

.         
. // Set regression variables
.         loc reg_race "cand_black zero_race cand_asian cand_hispa"

.         loc reg_sex "cand_female zero_sex"

.         loc reg_exp "cand_exp_teach cand_exp_council cand_exp_lawyer cand_exp_business zero_exp"

.         loc reg_biden "cand_biden_p59 cand_biden_p57 cand_biden_p55 cand_biden_p53 zero_biden"

.         loc reg_distpop "cand_dist1 cand_dist2 cand_dist3 cand_dist4 cand_dist5 cand_dist6 zero_dist"

.         loc reg_issues "cand_policy_abort1 cand_policy_abort2 cand_policy_tax1 cand_policy_tax2"

.         loc reg_issues "`reg_issues' cand_policy_health1 cand_policy_health2 cand_policy_eco1 zero_eco"

.         loc reg_affirm "cand_policy_aa1 cand_policy_aa2 cand_policy_aa3 zero_racepol"

.         loc reg_affirm2 "noracepolicy cand_policy_aa1 cand_policy_aa2 cand_policy_aa3 "

.         
. // Interactive Terms for Black Candidate X Affirmative Action
.         gen noracepolicy = cand_policy_aa1 == 0 & cand_policy_aa2 == 0 & cand_policy_aa3 == 0   

.         
.         gen dist_white = cand_dist4 == 1 | cand_dist5 == 1 | cand_dist6 == 1 | cand_dist7 == 1 

.         gen dist_black = cand_dist3 == 1

.                 // note baseline district is cand_dist7, [63, 8, 13, 11, 5]
.                 
.         
.         loc int ""

.         foreach r in white black asian hispa {
  2.                 gen `r'_aa1 = cand_policy_aa1*cand_`r'
  3.                 gen `r'_aa2 = cand_policy_aa2*cand_`r'
  4.                 gen `r'_aa3 = cand_policy_aa3*cand_`r'
  5.                 gen `r'_aa0 = noracepolicy*cand_`r'
  6.                 
.                 loc lab = proper("`r'")
  7.                 if "`lab'" == "Hispa" loc lab = "Hispanic"
  8.         
.                 label var `r'_aa0 "`lab' X No Position"
  9.                 label var `r'_aa1 "`lab' X Expand"
 10.                 label var `r'_aa2 "`lab' X Keep"
 11.                 label var `r'_aa3 "`lab' X End"
 12.                 
.                 loc int "`int' `r'_aa0 `r'_aa1 `r'_aa2 `r'_aa3"
 13.         
.         }

.         // set reference
.         replace white_aa0 = 0
(560 real changes made)

.         label var noracepolicy "Not shown position"

.         
.         gen out_fair_bwdiff = out_fair_black - out_fair_white
(2 missing values generated)

. 
.                 
. // Effect of candidate attributes on main outcomes, interacted
.         // Pooled
.         eststo clear

.         reg out_ideo `reg_race' `reg_affirm' `reg_issues' `reg_sex' cand_age `reg_exp' `reg_biden' if di
> st_white == 1, vce(cluster r_id)        
note: zero_race omitted because of collinearity.
note: zero_racepol omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: zero_sex omitted because of collinearity.
note: zero_exp omitted because of collinearity.
note: zero_biden omitted because of collinearity.

Linear regression                               Number of obs     =      4,165
                                                F(23, 1446)       =       7.27
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0368
                                                Root MSE          =     .23873

                                      (Std. err. adjusted for 1,447 clusters in r_id)
-------------------------------------------------------------------------------------
                    |               Robust
           out_ideo | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
         cand_black |   .0203188   .0087944     2.31   0.021     .0030676      .03757
          zero_race |          0  (omitted)
         cand_asian |   .0100722   .0098616     1.02   0.307    -.0092724    .0294168
         cand_hispa |   .0195213   .0095482     2.04   0.041     .0007916    .0382511
    cand_policy_aa1 |   .0126284   .0106826     1.18   0.237    -.0083266    .0335835
    cand_policy_aa2 |   .0181385   .0109462     1.66   0.098    -.0033336    .0396106
    cand_policy_aa3 |  -.0522481   .0107496    -4.86   0.000    -.0733346   -.0311616
       zero_racepol |          0  (omitted)
 cand_policy_abort1 |   .0735746    .011945     6.16   0.000     .0501432     .097006
 cand_policy_abort2 |   .0046543   .0111477     0.42   0.676    -.0172132    .0265217
   cand_policy_tax1 |   .0061314   .0116787     0.53   0.600    -.0167777    .0290405
   cand_policy_tax2 |   -.022972   .0114007    -2.01   0.044    -.0453357   -.0006084
cand_policy_health1 |   .0201619   .0119894     1.68   0.093    -.0033567    .0436804
cand_policy_health2 |  -.0083721    .011712    -0.71   0.475    -.0313466    .0146023
   cand_policy_eco1 |   .0043046   .0100926     0.43   0.670    -.0154932    .0241023
           zero_eco |          0  (omitted)
        cand_female |   .0145436   .0066084     2.20   0.028     .0015804    .0275067
           zero_sex |          0  (omitted)
           cand_age |  -.0007102   .0006053    -1.17   0.241    -.0018975    .0004772
     cand_exp_teach |    .012898   .0106358     1.21   0.225    -.0079653    .0337613
   cand_exp_council |   .0041592   .0101984     0.41   0.683    -.0158459    .0241644
    cand_exp_lawyer |  -.0017116   .0101829    -0.17   0.867    -.0216864    .0182633
  cand_exp_business |   .0018252   .0102516     0.18   0.859    -.0182844    .0219347
           zero_exp |          0  (omitted)
     cand_biden_p59 |  -.0093028   .0104088    -0.89   0.372    -.0297207    .0111152
     cand_biden_p57 |   .0144398   .0104122     1.39   0.166    -.0059847    .0348644
     cand_biden_p55 |  -.0082266   .0100202    -0.82   0.412    -.0278823     .011429
     cand_biden_p53 |   -.008231   .0103681    -0.79   0.427     -.028569     .012107
         zero_biden |          0  (omitted)
              _cons |   .6879029   .0363066    18.95   0.000     .6166837    .7591222
-------------------------------------------------------------------------------------

.         eststo ideo_w

.         reg out_ideo `reg_race' `reg_affirm' `reg_issues' `reg_sex' cand_age `reg_exp' `reg_biden' if di
> st_black == 1, vce(cluster r_id)        
note: zero_race omitted because of collinearity.
note: zero_racepol omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: zero_sex omitted because of collinearity.
note: zero_exp omitted because of collinearity.
note: zero_biden omitted because of collinearity.

Linear regression                               Number of obs     =      1,024
                                                F(23, 1023)       =       2.50
                                                Prob > F          =     0.0001
                                                R-squared         =     0.0510
                                                Root MSE          =     .24322

                                      (Std. err. adjusted for 1,024 clusters in r_id)
-------------------------------------------------------------------------------------
                    |               Robust
           out_ideo | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
         cand_black |  -.0025705   .0200694    -0.13   0.898    -.0419525    .0368114
          zero_race |          0  (omitted)
         cand_asian |   -.002522   .0212847    -0.12   0.906    -.0442887    .0392446
         cand_hispa |  -.0008927   .0221815    -0.04   0.968    -.0444191    .0426337
    cand_policy_aa1 |   .0329025   .0216242     1.52   0.128    -.0095303    .0753353
    cand_policy_aa2 |   .0263223   .0212304     1.24   0.215    -.0153377    .0679823
    cand_policy_aa3 |  -.0251988   .0213587    -1.18   0.238    -.0671107    .0167131
       zero_racepol |          0  (omitted)
 cand_policy_abort1 |     .12053   .0243604     4.95   0.000      .072728    .1683321
 cand_policy_abort2 |    .052252   .0233551     2.24   0.025     .0064226    .0980814
   cand_policy_tax1 |   .0055595   .0250962     0.22   0.825    -.0436865    .0548054
   cand_policy_tax2 |   -.009527    .024181    -0.39   0.694    -.0569771    .0379231
cand_policy_health1 |   .0500956   .0237066     2.11   0.035     .0035765    .0966146
cand_policy_health2 |   .0185004    .024181     0.77   0.444    -.0289496    .0659505
   cand_policy_eco1 |   .0310356   .0211046     1.47   0.142    -.0103776    .0724489
           zero_eco |          0  (omitted)
        cand_female |   .0029666   .0154907     0.19   0.848    -.0274307    .0333639
           zero_sex |          0  (omitted)
           cand_age |  -.0027072   .0013038    -2.08   0.038    -.0052656   -.0001487
     cand_exp_teach |   .0059687   .0247072     0.24   0.809    -.0425139    .0544514
   cand_exp_council |   .0129048   .0240533     0.54   0.592    -.0342947    .0601044
    cand_exp_lawyer |   .0216995   .0238184     0.91   0.362    -.0250389     .068438
  cand_exp_business |   .0177931   .0234252     0.76   0.448    -.0281738      .06376
           zero_exp |          0  (omitted)
     cand_biden_p59 |   .0049693   .0249221     0.20   0.842     -.043935    .0538736
     cand_biden_p57 |   .0097315   .0247096     0.39   0.694    -.0387559    .0582189
     cand_biden_p55 |   .0327758   .0248512     1.32   0.188    -.0159893     .081541
     cand_biden_p53 |   .0160714   .0241697     0.66   0.506    -.0313565    .0634993
         zero_biden |          0  (omitted)
              _cons |   .7168722   .0745504     9.62   0.000     .5705831    .8631614
-------------------------------------------------------------------------------------

.         eststo ideo_b

.         
.         reg out_fair_bwdiff `reg_race' `reg_affirm' `reg_issues' `reg_sex' cand_age `reg_exp' `reg_biden
> ' if dist_white == 1, vce(cluster r_id)
note: zero_race omitted because of collinearity.
note: zero_racepol omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: zero_sex omitted because of collinearity.
note: zero_exp omitted because of collinearity.
note: zero_biden omitted because of collinearity.

Linear regression                               Number of obs     =      4,167
                                                F(23, 1446)       =      10.96
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0670
                                                Root MSE          =     .37957

                                      (Std. err. adjusted for 1,447 clusters in r_id)
-------------------------------------------------------------------------------------
                    |               Robust
    out_fair_bwdiff | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
         cand_black |   .2073071   .0158317    13.09   0.000     .1762516    .2383626
          zero_race |          0  (omitted)
         cand_asian |   .0725276   .0151334     4.79   0.000     .0428419    .1022133
         cand_hispa |   .0950779   .0149927     6.34   0.000      .065668    .1244878
    cand_policy_aa1 |   .0566677   .0170446     3.32   0.001     .0232329    .0901025
    cand_policy_aa2 |   .0570246   .0167338     3.41   0.001     .0241994    .0898498
    cand_policy_aa3 |  -.0812953   .0161485    -5.03   0.000    -.1129723   -.0496183
       zero_racepol |          0  (omitted)
 cand_policy_abort1 |   .0037432    .018382     0.20   0.839    -.0323151    .0398014
 cand_policy_abort2 |   .0045166   .0181442     0.25   0.803    -.0310752    .0401084
   cand_policy_tax1 |   .0336276   .0175871     1.91   0.056    -.0008713    .0681265
   cand_policy_tax2 |   .0075541   .0173891     0.43   0.664    -.0265565    .0416646
cand_policy_health1 |   .0109656   .0185446     0.59   0.554    -.0254115    .0473428
cand_policy_health2 |    .018536   .0177437     1.04   0.296    -.0162701    .0533421
   cand_policy_eco1 |   .0318782   .0162484     1.96   0.050     5.25e-06    .0637512
           zero_eco |          0  (omitted)
        cand_female |   .0125485   .0106142     1.18   0.237    -.0082724    .0333693
           zero_sex |          0  (omitted)
           cand_age |  -.0002825   .0009319    -0.30   0.762    -.0021104    .0015454
     cand_exp_teach |  -.0057938   .0166731    -0.35   0.728    -.0384998    .0269123
   cand_exp_council |  -.0012204   .0162411    -0.08   0.940     -.033079    .0306381
    cand_exp_lawyer |  -.0091364   .0170743    -0.54   0.593    -.0426296    .0243567
  cand_exp_business |  -.0216218   .0166711    -1.30   0.195    -.0543239    .0110803
           zero_exp |          0  (omitted)
     cand_biden_p59 |  -.0093621   .0170835    -0.55   0.584    -.0428732    .0241491
     cand_biden_p57 |  -.0311825   .0168834    -1.85   0.065    -.0643011     .001936
     cand_biden_p55 |  -.0059492   .0165269    -0.36   0.719    -.0383685    .0264701
     cand_biden_p53 |  -.0152716   .0170179    -0.90   0.370     -.048654    .0181108
         zero_biden |          0  (omitted)
              _cons |  -.0366609   .0556796    -0.66   0.510    -.1458823    .0725605
-------------------------------------------------------------------------------------

.         eststo fair_bwdiff_w

.         reg out_fair_bwdiff `reg_race' `reg_affirm' `reg_issues' `reg_sex' cand_age `reg_exp' `reg_biden
> ' if dist_black == 1, vce(cluster r_id)
note: zero_race omitted because of collinearity.
note: zero_racepol omitted because of collinearity.
note: zero_eco omitted because of collinearity.
note: zero_sex omitted because of collinearity.
note: zero_exp omitted because of collinearity.
note: zero_biden omitted because of collinearity.

Linear regression                               Number of obs     =      1,025
                                                F(23, 1024)       =       2.34
                                                Prob > F          =     0.0004
                                                R-squared         =     0.0521
                                                Root MSE          =     .37705

                                      (Std. err. adjusted for 1,025 clusters in r_id)
-------------------------------------------------------------------------------------
                    |               Robust
    out_fair_bwdiff | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
         cand_black |   .1815437   .0324403     5.60   0.000     .1178867    .2452008
          zero_race |          0  (omitted)
         cand_asian |   .0584019   .0329412     1.77   0.077    -.0062381    .1230419
         cand_hispa |   .0333648   .0329178     1.01   0.311    -.0312293    .0979589
    cand_policy_aa1 |   .0168259   .0316293     0.53   0.595    -.0452398    .0788916
    cand_policy_aa2 |   .0362528   .0317262     1.14   0.253     -.026003    .0985086
    cand_policy_aa3 |   -.039803   .0321225    -1.24   0.216    -.1028364    .0232304
       zero_racepol |          0  (omitted)
 cand_policy_abort1 |   .0479932   .0388216     1.24   0.217    -.0281857    .1241721
 cand_policy_abort2 |   .0024761   .0348435     0.07   0.943    -.0658968     .070849
   cand_policy_tax1 |   .0228659   .0371796     0.62   0.539     -.050091    .0958227
   cand_policy_tax2 |   .0569832   .0376627     1.51   0.131    -.0169217    .1308881
cand_policy_health1 |   .0092144   .0376006     0.25   0.806    -.0645686    .0829973
cand_policy_health2 |   .0171546    .038316     0.45   0.654    -.0580322    .0923414
   cand_policy_eco1 |   .0142342   .0320154     0.44   0.657     -.048589    .0770575
           zero_eco |          0  (omitted)
        cand_female |   .0152657   .0240004     0.64   0.525    -.0318298    .0623613
           zero_sex |          0  (omitted)
           cand_age |   .0010177   .0020769     0.49   0.624    -.0030578    .0050933
     cand_exp_teach |  -.0135174   .0378579    -0.36   0.721    -.0878054    .0607706
   cand_exp_council |   .0410099   .0360261     1.14   0.255    -.0296835    .1117034
    cand_exp_lawyer |  -.0072526   .0357648    -0.20   0.839    -.0774334    .0629281
  cand_exp_business |   .0459507   .0369401     1.24   0.214    -.0265363    .1184377
           zero_exp |          0  (omitted)
     cand_biden_p59 |   .0247913   .0385546     0.64   0.520    -.0508636    .1004463
     cand_biden_p57 |   .0252249   .0366469     0.69   0.491    -.0466868    .0971366
     cand_biden_p55 |    .028797   .0417911     0.69   0.491     -.053209    .1108031
     cand_biden_p53 |   .0221612   .0392311     0.56   0.572    -.0548213    .0991437
         zero_biden |          0  (omitted)
              _cons |  -.0704354   .1200444    -0.59   0.558    -.3059965    .1651257
-------------------------------------------------------------------------------------

.         eststo fair_bwdiff_b

. 
.         coefplot (ideo_w, label() mc(teal) ciopts(color(teal) lw(med))) ///
>                          (ideo_b, label() mc(gs4) ciopts(color(gs4) lw(med))) ///
>                                 , bylabel("{bf:(a) Ideological Liberalness}") || ///
>                         (fair_bwdiff_w, label() mc(teal) ciopts(color(teal) lw(med))) ///
>                         (fair_bwdiff_b, label() mc(gs4) ciopts(color(gs4) lw(med))) ///
>                                 , bylabel("{bf:(b) Prioritize Black over White Constituents}") ///
>                         || , drop(_cons cand_age) ///
>                         omitted baselevels ms(c) msize(medsmall) ///
>                         ylabel(,labsize(vsmall)) ///
>                 xline(0, lc(black)) legend(order(2 "Majority-White Districts" 4 "Majority-Black District
> s") size(vsmall) pos(12))  ///
>                 subtitle(, bcolor(white) color(black) size(vsmall)) ///
>                 byopts(row(1) t1title("{bf:`title'}", size(small))) ///
>                 xtitle("Effects of Candidate Attributes (Scale 0 to 1)", size(vsmall)) ///
>                 xlabel(-0.2(0.1)0.2,labsize(small)) norecycle ///
>                 headings(cand_black = "{bf: Race}" ///
>                                 cand_female = "{bf: Gender}" ///
>                                 cand_exp_teach = "{bf: Occupation}" ///
>                                 cand_biden_p59 = "{bf: District Vote for Biden}" ///
>                                 cand_dist4 = "{bf: District Racial % [W,B,A,H,O]}" ///
>                                 cand_policy_abort1 = "{bf: Abortion}" ///
>                                 cand_policy_tax1 = "{bf: Tax Policy}" ///
>                                 cand_policy_health1 = "{bf: Healthcare}" ///
>                                 cand_policy_eco1 = "{bf: Energy}" ///
>                                 cand_policy_aa1 = "{bf: Affirmative Action}" ///
>                                 , labsize(vsmall)) 
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)

.         
.         graph display, xsize(4.5) ysize(3.4) margins(vsmall)    

.         graph export figure_s8.png, as(png) replace
(file figure_s8.png not found)
file figure_s8.png saved as PNG format

.         
.         
.         // Interacted
.         eststo clear

. 
.         reg out_ideo `reg_issues' `reg_sex' `reg_exp' `reg_biden' `int' cand_age if dist_white == 1, vce
> (cluster r_id)  
note: zero_eco omitted because of collinearity.
note: zero_sex omitted because of collinearity.
note: zero_exp omitted because of collinearity.
note: zero_biden omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      4,165
                                                F(32, 1446)       =       5.40
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0380
                                                Root MSE          =     .23884

                                      (Std. err. adjusted for 1,447 clusters in r_id)
-------------------------------------------------------------------------------------
                    |               Robust
           out_ideo | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
 cand_policy_abort1 |   .0737772   .0119964     6.15   0.000     .0502449    .0973095
 cand_policy_abort2 |   .0047911   .0111561     0.43   0.668    -.0170928    .0266749
   cand_policy_tax1 |   .0062419   .0116993     0.53   0.594    -.0167074    .0291913
   cand_policy_tax2 |  -.0235461   .0114449    -2.06   0.040    -.0459965   -.0010956
cand_policy_health1 |   .0197896   .0120303     1.64   0.100    -.0038091    .0433882
cand_policy_health2 |  -.0084706   .0117435    -0.72   0.471    -.0315068    .0145655
   cand_policy_eco1 |   .0040394   .0101238     0.40   0.690    -.0158196    .0238983
           zero_eco |          0  (omitted)
        cand_female |   .0147696    .006618     2.23   0.026     .0017876    .0277515
           zero_sex |          0  (omitted)
     cand_exp_teach |   .0127799   .0106803     1.20   0.232    -.0081706    .0337304
   cand_exp_council |   .0038664   .0102022     0.38   0.705    -.0161462     .023879
    cand_exp_lawyer |  -.0012641   .0102156    -0.12   0.902     -.021303    .0187748
  cand_exp_business |   .0013586   .0102729     0.13   0.895    -.0187929      .02151
           zero_exp |          0  (omitted)
     cand_biden_p59 |  -.0094083   .0104313    -0.90   0.367    -.0298703    .0110538
     cand_biden_p57 |   .0137366   .0104175     1.32   0.188    -.0066984    .0341716
     cand_biden_p55 |  -.0084006   .0100512    -0.84   0.403     -.028117    .0113158
     cand_biden_p53 |  -.0089261   .0103748    -0.86   0.390    -.0292775    .0114252
         zero_biden |          0  (omitted)
          white_aa0 |          0  (omitted)
          white_aa1 |  -.0100391   .0186018    -0.54   0.589    -.0465286    .0264503
          white_aa2 |   .0070848   .0193528     0.37   0.714    -.0308777    .0450474
          white_aa3 |   -.049745   .0191137    -2.60   0.009    -.0872385   -.0122514
          black_aa0 |   .0102881   .0171755     0.60   0.549    -.0234034    .0439796
          black_aa1 |   .0285476   .0174028     1.64   0.101    -.0055899     .062685
          black_aa2 |    .032231   .0184336     1.75   0.081    -.0039285    .0683905
          black_aa3 |  -.0422718   .0178242    -2.37   0.018    -.0772358   -.0073078
          asian_aa0 |  -.0123803   .0198925    -0.62   0.534    -.0514016    .0266409
          asian_aa1 |   .0234996     .01996     1.18   0.239     -.015654    .0626532
          asian_aa2 |   .0176796   .0207716     0.85   0.395    -.0230661    .0584253
          asian_aa3 |  -.0406396   .0203227    -2.00   0.046    -.0805047   -.0007744
          hispa_aa0 |   .0177637   .0195752     0.91   0.364    -.0206351    .0561625
          hispa_aa1 |   .0314559   .0202032     1.56   0.120    -.0081749    .0710867
          hispa_aa2 |    .036149   .0195666     1.85   0.065    -.0022329    .0745309
          hispa_aa3 |  -.0582125   .0213538    -2.73   0.006    -.1001002   -.0163247
           cand_age |  -.0007208   .0006066    -1.19   0.235    -.0019108    .0004691
              _cons |   .6966061   .0376096    18.52   0.000      .622831    .7703813
-------------------------------------------------------------------------------------

.         eststo ideo_w

.         reg out_ideo `reg_issues' `reg_sex' `reg_exp' `reg_biden' `int' cand_age if dist_black == 1, vce
> (cluster r_id)  
note: zero_eco omitted because of collinearity.
note: zero_sex omitted because of collinearity.
note: zero_exp omitted because of collinearity.
note: zero_biden omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      1,024
                                                F(32, 1023)       =       1.98
                                                Prob > F          =     0.0011
                                                R-squared         =     0.0544
                                                Root MSE          =     .24389

                                      (Std. err. adjusted for 1,024 clusters in r_id)
-------------------------------------------------------------------------------------
                    |               Robust
           out_ideo | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
 cand_policy_abort1 |   .1199761    .024444     4.91   0.000     .0720101    .1679422
 cand_policy_abort2 |   .0494278   .0236664     2.09   0.037     .0029875     .095868
   cand_policy_tax1 |   .0057997   .0252852     0.23   0.819     -.043817    .0554165
   cand_policy_tax2 |  -.0090304   .0244355    -0.37   0.712    -.0569797     .038919
cand_policy_health1 |   .0497455   .0240497     2.07   0.039     .0025531     .096938
cand_policy_health2 |   .0170541    .024455     0.70   0.486    -.0309337    .0650419
   cand_policy_eco1 |   .0309672   .0213225     1.45   0.147    -.0108737    .0728081
           zero_eco |          0  (omitted)
        cand_female |   .0026597   .0155784     0.17   0.864    -.0279095    .0332289
           zero_sex |          0  (omitted)
     cand_exp_teach |   .0052807   .0246658     0.21   0.831    -.0431207    .0536821
   cand_exp_council |   .0124138   .0241978     0.51   0.608    -.0350693    .0598969
    cand_exp_lawyer |   .0210894   .0240104     0.88   0.380     -.026026    .0682047
  cand_exp_business |   .0181629   .0239718     0.76   0.449    -.0288765    .0652024
           zero_exp |          0  (omitted)
     cand_biden_p59 |   .0052927   .0249187     0.21   0.832    -.0436049    .0541904
     cand_biden_p57 |   .0079725   .0247877     0.32   0.748    -.0406681    .0566131
     cand_biden_p55 |   .0326813   .0249932     1.31   0.191    -.0163626    .0817251
     cand_biden_p53 |   .0178895   .0243089     0.74   0.462    -.0298115    .0655906
         zero_biden |          0  (omitted)
          white_aa0 |          0  (omitted)
          white_aa1 |   .0453637   .0427497     1.06   0.289    -.0385234    .1292508
          white_aa2 |   .0230981    .040874     0.57   0.572    -.0571083    .1033045
          white_aa3 |   -.046652   .0409488    -1.14   0.255    -.1270053    .0337012
          black_aa0 |  -.0136981    .040525    -0.34   0.735    -.0932198    .0658236
          black_aa1 |    .042718    .042949     0.99   0.320    -.0415602    .1269963
          black_aa2 |   .0232314    .044135     0.53   0.599    -.0633742    .1098369
          black_aa3 |  -.0401229   .0432977    -0.93   0.354    -.1250853    .0448395
          asian_aa0 |   .0026676    .043164     0.06   0.951    -.0820325    .0873677
          asian_aa1 |  -.0105504   .0466612    -0.23   0.821    -.1021131    .0810123
          asian_aa2 |   .0296959   .0441252     0.67   0.501    -.0568903    .1162821
          asian_aa3 |  -.0095658   .0445573    -0.21   0.830    -.0969999    .0778682
          hispa_aa0 |  -.0052216   .0438638    -0.12   0.905    -.0912948    .0808517
          hispa_aa1 |   .0222949   .0474459     0.47   0.639    -.0708075    .1153972
          hispa_aa2 |   .0124061   .0452711     0.27   0.784    -.0764288    .1012409
          hispa_aa3 |   -.003744   .0499941    -0.07   0.940    -.1018467    .0943586
           cand_age |   -.002638   .0013168    -2.00   0.045     -.005222    -.000054
              _cons |   .7178029   .0784392     9.15   0.000     .5638829     .871723
-------------------------------------------------------------------------------------

.         eststo ideo_b

.         
.         reg out_fair_bwdiff `reg_issues' `reg_sex' `reg_exp' `reg_biden' `int' cand_age if dist_white ==
>  1, vce(cluster r_id)
note: zero_eco omitted because of collinearity.
note: zero_sex omitted because of collinearity.
note: zero_exp omitted because of collinearity.
note: zero_biden omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      4,167
                                                F(32, 1446)       =       8.30
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0688
                                                Root MSE          =     .37961

                                      (Std. err. adjusted for 1,447 clusters in r_id)
-------------------------------------------------------------------------------------
                    |               Robust
    out_fair_bwdiff | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
 cand_policy_abort1 |    .003214   .0183825     0.17   0.861    -.0328453    .0392733
 cand_policy_abort2 |   .0036748   .0181833     0.20   0.840    -.0319937    .0393433
   cand_policy_tax1 |   .0328547   .0176429     1.86   0.063    -.0017537    .0674631
   cand_policy_tax2 |   .0081689   .0174476     0.47   0.640    -.0260563    .0423941
cand_policy_health1 |   .0100696   .0185666     0.54   0.588    -.0263507      .04649
cand_policy_health2 |   .0175258   .0177472     0.99   0.324    -.0172872    .0523389
   cand_policy_eco1 |   .0312351   .0162888     1.92   0.055    -.0007172    .0631874
           zero_eco |          0  (omitted)
        cand_female |   .0121324   .0106621     1.14   0.255    -.0087824    .0330472
           zero_sex |          0  (omitted)
     cand_exp_teach |  -.0058515   .0167461    -0.35   0.727    -.0387007    .0269977
   cand_exp_council |  -.0008223   .0162888    -0.05   0.960    -.0327746      .03113
    cand_exp_lawyer |  -.0087721   .0170311    -0.52   0.607    -.0421804    .0246362
  cand_exp_business |  -.0210583   .0167574    -1.26   0.209    -.0539297    .0118132
           zero_exp |          0  (omitted)
     cand_biden_p59 |  -.0090389   .0171067    -0.53   0.597    -.0425955    .0245178
     cand_biden_p57 |  -.0319302   .0168603    -1.89   0.058    -.0650036    .0011431
     cand_biden_p55 |   -.005405   .0165756    -0.33   0.744    -.0379198    .0271098
     cand_biden_p53 |  -.0154123   .0170712    -0.90   0.367    -.0488991    .0180746
         zero_biden |          0  (omitted)
          white_aa0 |          0  (omitted)
          white_aa1 |   .0661504   .0284885     2.32   0.020     .0102672    .1220337
          white_aa2 |   .0915274   .0290711     3.15   0.002     .0345014    .1485535
          white_aa3 |  -.0836904   .0287767    -2.91   0.004    -.1401389   -.0272418
          black_aa0 |   .2258621    .028988     7.79   0.000      .168999    .2827251
          black_aa1 |   .2991614   .0293397    10.20   0.000     .2416085    .3567142
          black_aa2 |   .2467326   .0304773     8.10   0.000     .1869481     .306517
          black_aa3 |   .1272909   .0281794     4.52   0.000     .0720141    .1825677
          asian_aa0 |     .07449   .0279904     2.66   0.008     .0195839     .129396
          asian_aa1 |   .1118322   .0321227     3.48   0.001     .0488201    .1748443
          asian_aa2 |   .1540306   .0318658     4.83   0.000     .0915226    .2165387
          asian_aa3 |   .0247854   .0302068     0.82   0.412    -.0344683    .0840392
          hispa_aa0 |   .1169393   .0279895     4.18   0.000      .062035    .1718436
          hispa_aa1 |   .1504697   .0316389     4.76   0.000     .0884067    .2125326
          hispa_aa2 |   .1534095   .0305903     5.01   0.000     .0934033    .2134157
          hispa_aa3 |   .0319334   .0303451     1.05   0.293    -.0275918    .0914586
           cand_age |  -.0002945   .0009332    -0.32   0.752    -.0021251     .001536
              _cons |  -.0453488   .0584613    -0.78   0.438    -.1600268    .0693291
-------------------------------------------------------------------------------------

.         eststo fair_bwdiff_w

.         reg out_fair_bwdiff `reg_issues' `reg_sex' `reg_exp' `reg_biden' `int' cand_age if dist_black ==
>  1, vce(cluster r_id)
note: zero_eco omitted because of collinearity.
note: zero_sex omitted because of collinearity.
note: zero_exp omitted because of collinearity.
note: zero_biden omitted because of collinearity.
note: white_aa0 omitted because of collinearity.

Linear regression                               Number of obs     =      1,025
                                                F(32, 1024)       =       1.92
                                                Prob > F          =     0.0017
                                                R-squared         =     0.0570
                                                Root MSE          =     .37778

                                      (Std. err. adjusted for 1,025 clusters in r_id)
-------------------------------------------------------------------------------------
                    |               Robust
    out_fair_bwdiff | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
 cand_policy_abort1 |   .0490463     .03895     1.26   0.208    -.0273847    .1254772
 cand_policy_abort2 |    .003788   .0349506     0.11   0.914     -.064795     .072371
   cand_policy_tax1 |   .0234074   .0373489     0.63   0.531    -.0498817    .0966966
   cand_policy_tax2 |   .0585135   .0377691     1.55   0.122    -.0156001    .1326271
cand_policy_health1 |   .0088942   .0381594     0.23   0.816    -.0659854    .0837738
cand_policy_health2 |   .0177288    .038375     0.46   0.644    -.0575738    .0930315
   cand_policy_eco1 |   .0173021   .0323841     0.53   0.593    -.0462447    .0808488
           zero_eco |          0  (omitted)
        cand_female |   .0157359    .024025     0.65   0.513    -.0314079    .0628797
           zero_sex |          0  (omitted)
     cand_exp_teach |  -.0142613   .0378057    -0.38   0.706    -.0884468    .0599241
   cand_exp_council |   .0354767   .0365598     0.97   0.332     -.036264    .1072175
    cand_exp_lawyer |  -.0109539   .0358849    -0.31   0.760    -.0813702    .0594625
  cand_exp_business |   .0398101   .0376803     1.06   0.291    -.0341293    .1137496
           zero_exp |          0  (omitted)
     cand_biden_p59 |   .0273833   .0386894     0.71   0.479    -.0485362    .1033029
     cand_biden_p57 |   .0268417   .0370868     0.72   0.469    -.0459332    .0996166
     cand_biden_p55 |   .0311899   .0419418     0.74   0.457    -.0511118    .1134915
     cand_biden_p53 |   .0232196   .0397202     0.58   0.559    -.0547226    .1011619
         zero_biden |          0  (omitted)
          white_aa0 |          0  (omitted)
          white_aa1 |  -.0259778    .064106    -0.41   0.685    -.1517719    .0998163
          white_aa2 |   -.028506   .0608749    -0.47   0.640    -.1479597    .0909478
          white_aa3 |   -.090743   .0584466    -1.55   0.121    -.2054317    .0239457
          black_aa0 |    .129027   .0572293     2.25   0.024     .0167269    .2413271
          black_aa1 |   .1554037   .0587763     2.64   0.008     .0400678    .2707395
          black_aa2 |   .1959365   .0595409     3.29   0.001     .0791004    .3127725
          black_aa3 |   .0967569   .0630065     1.54   0.125    -.0268797    .2203934
          asian_aa0 |   -.003969   .0595498    -0.07   0.947    -.1208225    .1128844
          asian_aa1 |  -.0100257   .0596797    -0.17   0.867    -.1271342    .1070827
          asian_aa2 |   .0783968   .0591363     1.33   0.185    -.0376453     .194439
          asian_aa3 |   .0319623   .0582892     0.55   0.584    -.0824176    .1463423
          hispa_aa0 |  -.0257128   .0489394    -0.53   0.599    -.1217459    .0703202
          hispa_aa1 |   .0609634   .0610378     1.00   0.318    -.0588101     .180737
          hispa_aa2 |   .0228735   .0615425     0.37   0.710    -.0978904    .1436373
          hispa_aa3 |  -.0825472   .0727716    -1.13   0.257    -.2253458    .0602514
           cand_age |   .0010581   .0020753     0.51   0.610    -.0030142    .0051303
              _cons |  -.0325584   .1220793    -0.27   0.790    -.2721127    .2069958
-------------------------------------------------------------------------------------

.         eststo fair_bwdiff_b

.         
.         coefplot (ideo_w, label() mc(teal) ciopts(color(teal) lw(med))) ///
>                          (ideo_b, label() mc(gs4) ciopts(color(gs4) lw(med))) ///
>                                 , bylabel("{bf:(a) Ideological Liberalness}") || ///
>                         (fair_bwdiff_w, label() mc(teal) ciopts(color(teal) lw(med))) ///
>                         (fair_bwdiff_b, label() mc(gs4) ciopts(color(gs4) lw(med))) ///
>                                 , bylabel("{bf:(b) Prioritize Black over White Constituents}") ///
>                         || , drop(_cons `reg_sex' `reg_issues' cand_age `reg_exp' `reg_biden') ///
>                         omitted baselevels ms(c) msize(medsmall) ///
>                         ylabel(,labsize(vsmall)) ///
>                 xline(0, lc(black)) legend(order(2 "Majority-White Districts" 4 "Majority-Black District
> s") size(vsmall))  ///
>                 subtitle(, bcolor(white) color(black) size(vsmall)) ///
>                 byopts(row(1) t1title("{bf:`title'}", size(small))) ///
>                 xtitle("Effects of Candidate Attributes (Scale 0 to 1)", size(vsmall)) ///
>                 xlabel(-0.2(0.1)0.2,labsize(small)) norecycle ///
>                 headings(white_aa0 = "{bf: White X Affirmative Action}" ///
>                                 black_aa0 = "{bf: Black X Affirmative Action}" ///
>                                 asian_aa0 = "{bf: Asian X Affirmative Action}" ///
>                                 hispa_aa0 = "{bf: Hispanic X Affirmative Action}" ///
>                                 , labsize(vsmall)) 
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style med not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)
(note:  named style c not found in class symbol, default attributes used)

. 
. 
.         
.         graph display, xsize(4.5) ysize(3.4) margins(vsmall)    

. 
.         graph export figure_s9.png, as(png) replace                     
(file figure_s9.png not found)
file figure_s9.png saved as PNG format

.                 
.         
. 
end of do-file

. 
. 
. // Clean up extraneous files from outreg and graphing
. fs *.txt
table_s1b.txt             table_s2_fig2results.txt  table_s4_fig3results.txt
table_s1_fig1results.txt  table_s3.txt              table_s5_fig4results.txt

. foreach f in `r(files)' {
  2.         erase `f'
  3. }

. 
. fs *.gph
fig1.gph                   f_out_priority_abort.gph   f_out_priority_sj.gph
fig2.gph                   f_out_priority_crim.gph    f_out_priority_tax.gph
fig_ep.gph                 f_out_priority_enviro.gph  lucid.gph
fig_rr.gph                 f_out_priority_health.gph  s1_1.gph
f_out_fair_bwdiff.gph      f_out_priority_job.gph     s1_2.gph

. foreach f in `r(files)' {
  2.         erase `f'
  3. }

. 
. fs *.tmp

. foreach f in `r(files)' {
  2.         erase `f'
  3. }

. 
. log close
      name:  <unnamed>
       log:  C:\Users\wujen\Dropbox\S_CandidateRaceIdeology\Replication Archive\masterlog.log
  log type:  text
 closed on:  22 Aug 2024, 10:52:09
----------------------------------------------------------------------------------------------------------
